Millimeter-wave (mmWave) radar has emerged as a powerful sensing modality for human activity recognition (HAR) owing to its capability to capture 3D point cloud sequences without privacy concerns. However, effectively modeling the sparse, irregular, and non-uniform nature of radar data remains a major challenge. Existing approaches often rely on highly complex network architectures to improve accuracy, which leads to excessive computational overhead and poor scalability. To overcome these limitations, this paper proposes a compact hybrid feature extraction network for voxelized radar point cloud classification, which performs early-stage spatio-temporal fusion and is termed STFusionNet (Spatial-Temporal Fusion Network). The STFusionNet comprises (i) a lightweight 3D convolutional front-end, which treats consecutive temporal frames as input channels to encode motion dynamics into a compact volumetric representation and further aggregates features along the depth axis; (ii) a minimalist 2D convolutional backbone after a Depth-to-Channel Folding operation, which captures spatial features with minimal computational cost. Extensive experiments on the public MMActivity and MiliPoint datasets demonstrate that our model achieves competitive accuracy (e.g., 92.20% on MMActivity and 72.86% on MiliPoint) with only about 50K parameters and 46 MMac, outperforming or matching representative spatio-temporal baselines under a much lower computational budget. Extensive ablation experiments verify the contribution of key components, while statistical significance tests confirm the reliability of the performance improvements. These results confirm that STFusionNet offers a robust, efficient, and generalizable solution for mmWave radar-based HAR in Internet of Things (IoT) applications.

In this paper, we analyze the role of fluid antenna systems (FAS) in multi-user systems with hardware impairments (HIs). Specifically, we investigate a scenario where a base station (BS) equipped with multiple fluid antennas communicates with multiple communication users (CUs), each equipped with a single fluid antenna. Our objective is to maximize the minimum communication rate among all users by jointly optimizing the BS's transmit beamforming, the positions of its transmit fluid antennas, and the positions of the CUs' receive fluid antennas. To address this non-convex problem, we propose a block coordinate descent (BCD) algorithm integrating semidefinite relaxation (SDR), rank-one constraint relaxation (SRCR), successive convex approximation (SCA), and majorization-minimization (MM). Simulation results demonstrate that FAS significantly enhances system performance and robustness, with notable gains when both the BS and CUs are equipped with fluid antennas. Even under low transmit power conditions, deploying FAS at the BS alone yields substantial performance gains. However, the effectiveness of FAS depends on the availability of sufficient movement space, as space constraints may limit its benefits compared to fixed antenna strategies. Our findings highlight the potential of FAS to mitigate HIs and enhance multi-user system performance, while emphasizing the need for practical deployment considerations.

Artificial noise (AN) has been recognized as an effective physical-layer security scheme impairing the eavesdropper (Eve). Recently, artificial noise elimination (ANE) has emerged as a promising strategy to mitigate the impact of AN at Eves. However, conventional ANE schemes rely on prior knowledge, such as legitimate channel state information (CSI) or classification information, which may limit their practical applicability. To address these practical challenges, we propose an ANE scheme beyond prior knowledge (BPK) by leveraging machine learning algorithms. Firstly, a coarse projection is applied to partially eliminate the impact of AN using maximum likelihood estimation on the equivalent AN matrix. Secondly, a density clustering algorithm is introduced to obtain classification information based on the coarsely-projected observed vectors. Thirdly, a generalized principal component analysis (PCA)-based ANE algorithm is developed to effectively mitigate the residual AN using the obtained classification information. Furthermore, the artificial-noise-to-signal ratio (ANSR) and computational complexity are analyzed for performance revaluation, and a redefinition of several AN design principles is provided for scenarios involving a powerful Eve equipped with the BPK-ANE scheme by deriving the validity boundary. Finally, numerical results reveal key insights into four principles of AN: 1) Allocating less power to AN; 2) Reducing the randomness of AN; 3) Increasing the number of transmit antennas; and 4) Increasing the modulation order.

Massive multiple-input multiple-output (MIMO) array systems are a cornerstone technology for beyond fifth-generation (B5G) and sixth-generation (6G) wireless communications. This paper proposes a novel algorithm for the joint estimation of direction-of-departure (DOD) and direction-of-arrival (DOA) in massive MIMO systems under unknown gain-phase errors. The proposed method first exploits a normalized rotational invariance property to extract the relative amplitude-phase difference vectors between adjacent antenna elements. By incorporating the prior knowledge that the transmitter and receiver phase errors follow a zero-mean distribution, we formulate two decoupled cost functions to enable joint DOD and DOA estimation. We then obtain that the corresponding angular parameters efficiently through low-complexity spectral searches. Notably, the proposed method requires only one well-calibrated transmitter and one well-calibrated receiver, thereby substantially reducing the calibration effort compared with existing approaches. The gain errors are directly estimated from the amplitude-phase difference vectors, while the phase error vectors are reconstructed using the estimated DOD and DOA values. The proposed framework accommodates general conformal transceiver array geometries and effectively mitigates error accumulation in gain-phase calibration. Simulation results verify that the proposed algorithm achieves superior angular estimation accuracy and calibration precision compared with state-of-the-art techniques.

Fluid antenna systems (FAS) are emerging as a transformative enabler for sixth-generation (6G) wireless communications, providing unprecedented spatial diversity through dynamic reconfiguration of antenna ports. However, the inherent spatial correlation among ports poses significant challenges for accurate analysis. Conventional models such as Jakes are analytically intractable, while oversimplified constant-correlation models fail to capture the true behavior. In this work, we address these challenges by applying the variable block-correlation model (VBCM) -- originally proposed by Ramírez-Espinosa \textit{et al.} in 2024 -- to FAS security analysis, and by developing comprehensive optimization methods to enhance analytical accuracy. We derive new closed-form expressions for average secrecy capacity (ASC) and secrecy outage probability (SOP), demonstrating that the VBCM framework achieves simulation-aligned accuracy, with relative errors consistently below $5\%$ (compared to $10$--$15\%$ for constant-correlation models). To maximize ASC, we further design two algorithms: a grid search (GS) method and a gradient descent (GD) method. Numerical results reveal that the VBCM-based approach not only provides reliable insights into FAS security performance, but also yields substantial gains -- ASC improvements exceeding $120\%$ in high-threat scenarios and $18$--$19\%$ performance enhancements for compact antenna configurations. These findings underscore the practical value of integrating VBCM into FAS security analysis and optimization, establishing it as a powerful tool for advancing 6G communication systems.

Automatic modulation classification (AMC) is a key technique for identifying the modulation schemes of wireless signals, enabling improved performance and security in communication systems by accurately classifying signal types. However, most existing AMC research assumes modulation classes are part of a closed set, which can cause classifiers to misidentify unknown modulation schemes as known ones, undermining both the security and reliability of communication systems. To address this, we propose a novel open set AMC (OS-AMC) method based on deep metric learning and OpenMax (M-OpenMax). The proposed M-OpenMax-based OS-AMC method utilizes crossentropy loss and center loss to extract separable and discriminative signal features and uses OpenMax to adjust the nonnormalized score output of the model to achieve the classification of known signals and removal of unknown signals. Experimental results demonstrate that the proposed M-OpenMax-based OSAMC method outperforms other open-set AMC techniques, particularly in its ability to handle unknown modulation types.

Cell-free massive multiple-input multiple-output (CF-mMIMO) system has been attracting much attention as a key technology for beyond-fifth-generation (B5G) systems. A CF-mMIMO system serves users by coordinating a large number of distributed antennas deployed over the service area and can effectively address the blockage problem in the millimeter-wave and terahertz frequency bands, thereby enabling reliable communication. Furthermore, cluster-centric CF-mMIMO system, which groups antennas and users into multiple clusters, was proposed to reduce computational complexity. However, inter-cluster interference (ICI) significantly degrades the link capacity. Additionally, the use of omnidirectional antennas in cluster-centric CF-mMIMO results in substantial optical mobile fronthaul load, making practical implementation challenging. To address these issues, this paper proposes an array-antenna-based cluster-centric CF-mMIMO system. The proposed CF-mMIMO system is compared with the omnidirectional-antenna-based CF-mMIMO system. Simulation results demonstrate that the use of array antennas effectively mitigates ICI with a lower cost of optical fiber deployment, offering a more feasible and efficient impiementation of ciuster-centric CF-mMIMO.

Specific emitter identification (SEI) is crucial in the Internet of Everything (IoE). Over the past decade, deep learning (DL) and broad learning (BL)-enabled SEI technologies have emerged. Recently, many researchers have begun exploring semi-supervised learning techniques to address the semi-supervised SEI (SS-SEI) problem with limited labeled RF signals. However, existing SS-SEI solutions often prioritize identification performance, leading to high computational overheads and lacking iterability. To overcome these challenges, this paper proposes a novel SS-SEI solution based on a learnable broad learning network (LBL). Initially, a pretrained DL-based SEI model is downloaded to the edge device. Meanwhile, an updatable BL-based SEI method is deployed locally on the edge device to identify unlabelled signals. When the LBL solution is operational, edge devices capture real-time unlabelled RF signals. The pretrained DL-based SEI method and the locally BL-based SEI method jointly identify these RF signals. The identification results and the new real-time RF signals are then used to update the weights of the BL-based SEI method at the edge devices. The LBL SS-SEI solution is validated using an open-source, large-scale, real-world automatic dependent surveillance-broadcast (ADS-B) dataset. Experimental results demonstrate that the proposed LBL solution offers significant advantages regarding SS-SEI performance.

In this article, a novel multiuser multiple-input-multiple-output (MIMO) communication system for Internet of Things (IoT) is proposed, where the aerial reconfigurable intelligent surface (ARIS) and nonorthogonal multiple access (NOMA) are used as the sum rate enhancement pathway. The base station (BS) has multiple antennas that transmit superimposed signals to multiple users. The passive ARIS serves as a flexible transmit relay to reduce path loss and improve channel gains. Users are divided into several groups based on their channel status, each sharing a radio frequency (RF) chain. To maximize the sum rate of all users, the placement of ARIS, the passive/active beamforming design and the power allocation among users are jointly optimized. As the joint optimization for user grouping, passive/active beamforming and power distribution is formulated as a mixed-integer nonlinear program (MINLP) which is nonconvex and coupled and hence, obtaining an optimal solution is challenging. In this article, the problem is decoupled into three subproblems and solved alternately efficiently. The numerical results demonstrate that the suggested MIMO-ARIS-NOMA system can achieve higher sum rate performance than traditional schemes.

In simulating synthetic aperture radar (SAR) ship wakes, dynamic wake modeling often uses the linear superposition of sea waves and Kelvin wakes. This method, however, overlooks the alterations in sea surface roughness caused by the nonlinear interaction between waves and wakes, thus failing to accurately capture real sea surface variations. In this letter, we introduce a rapid SAR image simulation technique for ship wakes that incorporates sea waves using fluid velocity potential. Firstly, the computational domain and ship grid are constructed, with the grid scale tailored to the ship's surface structure to satisfy boundary conditions for efficient fluid velocity potential calculations. Next, to enhance boundary calculation accuracy, we employ the Taylor expansion boundary element method to swiftly resolve both steady and unsteady velocity potential components. Additionally, our approach not only depicts the interaction between sea waves and ship wakes but also facilitates the simulation analysis of various sea condition parameters. By treating the ship wake as noise and comparing images containing only background sea waves with the simulation images, the results show that the accuracy of the proposed approach is 0.2 SSIM higher than that of the linear superposition method, and the speed is 3 hours faster than that of CFD method.

In this paper, we conduct a theoretical analysis of how to integrate reconfigurable intelligent surfaces (RIS) with cooperative non-orthogonal multiple access (NOMA), considering URLLC. We consider a downlink two-user cooperative NOMA system employing short-packet communications, where the two users are denoted by the central user (CU) and the cell-edge user (CEU), respectively, and an RIS is deployed to enhance signal quality. Specifically, compared to CEU, CU lies nearer from BS and enjoys the higher channel gains. Closed-form expressions for the CU’s average block error rate (BLER) are derived. Furthermore, we evaluate the CEU’s BLER performance utilizing selective combining (SC) and derive a tight lower bound under maximum ratio combining (MRC). Simulation results are provided to our analyses and demonstrate that the RIS-assisted system significantly outperforms its counterpart without RIS in terms of BLER. Notably, MRC achieves a squared multiple of the diversity gain of the SC, leading to more reliable performance, especially for the CEU. Furthermore, by dividing the RIS into two zones, each dedicated to a specific user, the average BLER can be further reduced, particularly for the CEU.

Specific emitter identification (SEI) has emerged as a notable device authentication technology, distinguishing various emitters through the unique radio frequency fingerprint (RFF) inherent in wireless devices. Traditional SEI methods, often hindered by time-consuming manual feature extraction, struggle with complex encrypted signals. The advent of deep learning, with its robust feature extraction capabilities, has significantly advanced SEI, yet it typically demands extensive radio frequency signal samples and falters with limited (i.e., few-shot) samples. Our proposed few-shot SEI (FS-SEI) approach, integrating neural architecture search (NAS) and deep transfer learning (DTL), adeptly identifies few-shot long range (LoRa) devices. This method begins with NAS to autonomously tailor optimal network architectures for SEI tasks, followed by pre-training on extensive auxiliary datasets to extract general RFF features of LoRa devices. Transfer learning then fine-tunes these features for distinctiveness with compact intra-class distances. By only utilizing few-shot LoRa data for final parameter adjustments, the classifier rapidly assimilates new categories. Simulations confirm our FS-SEI method's superior accuracy over classical approaches, with visualized feature analysis underscoring its distinguishing and generalizing prowess.

In a cellular distributed multiuser MIMO (MU- MIMO) system, inter-cluster interference suppression is a challenge because user-cluster-wise distributed MU-MIMO is performed using the same radio resources in all user-clusters in each cell. Recently, we proposed the interference suppression multiuser minimum mean square error (IS-MU-MMSE) multiplexing for the single-antenna users case. In this paper, we extend IS-MU-MIMO multiplexing to the multiple-antenna users case. As the number of antennas per user increases, each user can transmit multiple streams using eigenmode transmission, however, the number of distributed antennas required increases and the antenna degrees of freedom for inter- cluster interference suppression decreases. We propose the IS- MU-MMSE multiplexing combined with optimal joint transmit/receive diversity (JTRD), where the concept of a virtual single antenna user is introduced, the number of required minimum distributed antennas at the base station is reduced to equal to the number of users, and the remaining antenna degrees of freedom are used for inter-cluster interference suppression. Through computer simulations, we evaluate the uplink user capacity and confirm that, in a high user-density environment, IS-MU-MMSE multiplexing combined with optimal JTRD is superior to that combined with eigenmode transmission.

Radar emitter identification (REI) is a crucial function of electronic radar warfare support systems. The challenge emphasizes identifying and locating unique transmitters, avoiding potential threats, and preparing countermeasures. Due to the remarkable effectiveness of deep learning (DL) in uncovering latent features within data and performing classifications, deep neural networks (DNNs) have seen widespread application in REI. In many real-world scenarios, obtaining a large number of annotated radar transmitter samples for training identification models is essential yet challenging. Given the issues of insufficient labeled datasets and abundant unlabeled training datasets, we propose a novel REI method based on a semi-supervised learning (SSL) framework with virtual adversarial training (VAT). Specifically, two objective functions are designed to extract the semantic features of radar signals: computing cross-entropy loss for labeled samples and virtual adversarial training loss for all samples. Additionally, a pseudo-labeling approach is employed for unlabeled samples. The proposed VAT-based SS-REI (SS-VAT) method is evaluated on a radar dataset. Simulation results indicate that the proposed SS-VAT method outperforms the latest SS-REI method in recognition performance.

In this article, a hybrid radio frequency-visible light communication and positioning (RF-VLCP) system is designed, which can support high-data rate communication and high accuracy positioning with good energy efficiency (EE) performance. The hybrid system uses two links for downlink communication, namely, radio frequency (RF) and visible light communication (VLC) links, and employs visible light positioning (VLP) technology for positioning. Furthermore, an optimization problem is developed to allocate power for VLC and VLP links and to design beamformer for the RF transmitter. By doing so, the EE of the hybrid system is maximized while the Cramer–Rao Lower bound (CRLB) of the positioning error and the minimum data rate of the communication are guaranteed. A two-step algorithm is proposed to tackle the formulated optimization problem, which first determines the power allocation of the VLP signal and then obtains the power allocation of the VLC signal and the beamformer of the RF transmitter. Numerical results demonstrate the advantages of the proposed two-step algorithm over the existing algorithm in terms of computation speed. In addition, the EE performance of the hybrid system is evaluated under different data rate and positioning accuracy requirements. Besides, we also show that the hybrid RF-VLCP system is more energy efficient compared to standalone RF and VLP technologies.

The success of the Internet of Things has recently spread to the industrial sector, commonly referred to as Industrial IoT (IIoT). IIoT, which has a far-reaching impact on the operation of industries around the world, is recognized as a key enabler for the fourth industrial revolution. It has the potential to prompt economic growth and global competitiveness, in terms of improving productivity, efficiency, and so on.

Direction-of-arrival (DOA), also referred to as angle-of-arrival (AOA), is an excellent choice for unmanned aerial vehicle (UAV) localization and has garnered significant attention recently. In this article, we propose a novel two-dimensional (2D)-DOA auxiliary framework for anonymous UAV localization. At its core, this framework relies on measuring 2D-DOA using a monostatic multiple-input–multiple-output (MIMO) radar configured with electromagnetic vector sensors (EMVSs). Differing from existing mainstream methods, the multipath effect of the UAV is taken into account. A rearrangement multiple signal classification (R-MUSIC) algorithm is developed. The algorithm recovers the covariance matrix rank by connecting spatial responses from both transmitting (Tx) or receiving (Rx) arrays with radar cross-section (RCS) coefficients. Subsequently, rough 2D-DOA estimates are obtained using the vector cross-product (VCP) technique. These rough estimates are then used to establish good initialized values for refined 2-D spectral peak searching. Finally, leveraging the relationship between 2D-DOA and Tx/Rx array coordinates, a UAV’s 3-D position can be directly computed. This framework remains insensitive to the geometric configuration of Tx/Rx arrays while striking a balance between complexity and accuracy. Numerical simulation experiments confirm the improvements of our developed R-MUSIC algorithm.

The increasing significance of unmanned aerial vehicles (UAVs) in mobile edge computing (MEC) has captured considerable attention. Nevertheless, the effectiveness of UAVs-assisted MEC networks is hampered by challenges, such as limited communication capacity and onboard power. To tackle these issues, this study develops a constrained multiobjective optimization model designed to enhance the performance of UAVs-assisted MEC networks, focusing on system capacity, energy consumption, and task latency. As a result, this problem manifests as a complex constrained multiobjective optimization problem. The study then proposes a constrained multiobjective decomposition evolutionary algorithm (CMODEA) with low-computational complexity. This algorithm employs an adaptive individual comparison strategy, balancing diversity and convergence, and integrates an optimally guided differential evolution strategy for efficiently approximating optimal solutions. Additionally, it incorporates an adaptive constraint handling method, effectively managing existing constraints. The CMODEA aims to simultaneously optimize system capacity, energy consumption, and task latency while meeting the computational resource requirements of UAVs and ensuring acceptable user task latency levels. Simulation results demonstrate the algorithm’s effectiveness in significantly enhancing capacity, reducing energy consumption and latency, without greatly increasing algorithm complexity.

This article proposes a new framework of aerial reconfigurable intelligent surface (ARIS) enhancing the nonorthogonal multiple access (NOMA) system. The base station (BS) transmits superimposed signals to multiple users with different channel gains through ARIS which can flexibly change channel conditions and perform intelligent NOMA operations. It ensures that our system can perform well in providing services to multiple users simultaneously. In this system, the placement of the unmanned aerial vehicle (UAV) is jointly optimized along with the AIRS passive beam and the multiuser power allocation in order to maximize the communication sum rate. Since the joint optimization problem is nonconvex and coupled, it is hence disintegrated into three subproblems and it is solved alternately through the successive convex approximation (SCA). Moreover, semi definite programming (SDP) is used to deal with the rank one constraint of RIS reflection matrix and comparisons are made using particle swarm optimization (PSO). The numerical results show that the proposed ARIS-NOMA framework can achieve better sum rate performance than traditional NOMA with fixed RIS and OMA-ARIS.

The wake target has garnered increasing attention due to its length, which can be up to ten times that of the ship, and its inclusion of critical navigation information such as heading and speed. However, deep learning methods used in synthetic aperture radar (SAR) image wake detection tasks are limited to analyzing the features of the image itself, overlooking the characteristics of ship wakes in the frequency domain. This letter proposes a network called pseudo-siamese and multidomain feature fusion network (PSMDNet) that is composed of two parallel feature extraction branches. The feature extraction in the frequency domain uses the frequency channel attention network (FcaNet) as the backbone, incorporating an adjacent scale space attention module (ASSAM) to fuse high-level features into low-level features. The time domain uses the residual network (ResNet) as the backbone, incorporating a bidirectional feature channel module (BFCM) to enhance the representation of low-level spatial information. These two parallel branches extract the time- and frequency-domain features from the image to better capture the wake feature information. The proposed ASSAM module calculates weighted coding with context information, thereby selectively aggregating the unique linear spatial features of the wake into the low-level feature map. Verification experiments were conducted on the SAR-WAKE dataset, and the results demonstrate that the proposed method excels in detection accuracy compared with other algorithms, achieving excellent results of 92.71%. Particularly noteworthy is that the positioning and visualization of wake vertex and Kelvin arms are realized by the loss function designed for the wake.

Intelligent Reflecting Surface (IRS) represents a significant breakthrough in wireless communications, allowing the reconstruction of wireless channels even for occluded users to the base station (BS). Estimating the Direction-of-Arrival (DOA) of a source oriented toward Non-Line-of-Sight (NLOS) propagation is an intriguing topic in an IRS-aided wireless communication scenario. However, the existing optimization-based approaches are overly complex to be practically implemented. In this paper, we propose a polarized IRS architecture, in which both IRS and BS are equipped with arbitrarily placed Electromagnetic Vector Sensor (EMVS) arrays. A Normalized Vector-Cross Product (NVCP) estimator is developed for DOA estimation, which avoids the need for complicated data recovery or exhaustive grid search. The proposed framework enables Two-Dimensional (2D) DOA estimation for NLOS signals without requiring prior knowledge of the BS-IRS channel. Numerical simulations have been conducted to verify its effectiveness.

Rogue emitter detection (RED) is a crucial technique to maintain secure internet of things applications. Existing deep learning-based RED methods have been proposed under friendly environments. However, these methods perform unstably under low signal-to-noise ratio (SNR) scenarios. To address this problem, we propose a robust RED method, which is a hybrid network of denoising autoencoder and deep metric learning (DML). Specifically, denoising autoencoder is adopted to mitigate noise interference and then improve its robustness under low SNR while DML plays an important role to improve the feature discrimination. Several typical experiments are conducted to evaluate the proposed RED method on an automatic dependent surveillance-Broadcast dataset and an IEEE 802.11 dataset and also to compare it with existing RED methods. Simulation results show that the proposed method achieves better RED performance and higher noise robustness with more discriminative semantic vectors than existing methods.

In user-initiated multiuser joint transmit-receive diversity (JTRD), each user equipment (UE) determines its diversity weight vector based on its own multi-input multi-output (MIMO) channel matrix and transmits pilot precoded by its diversity weight vector. Then, the base station (BS) obtains the equivalent multiuser MIMO channel matrix (which is a concatenation of user side diversity weight vector matrix and multiuser MIMO channel) and determines its multiuser JTRD weight matrix. There are suboptimal and optimal multiuser JTRDs. In the former, each UE determines its JTRD weight vector based on its own MIMO channel matrix. In the latter case, each UE applies the singular value decomposition (SVD) to its MIMO channel and determines the largest eigen vector as its JTRD weight vector. We show that in a strongly asymmetric MIMO fading channel (i.e., the number of BS antennas is considerably larger than that of UE antennas), the suboptimal JTRD using the selection weight vector provides a slightly higher diversity gain than that using the maximal-ratio weight vector and that the transmission performance difference between the suboptimal and optimal multiuser JTRDs is small.

To reduce the outage of the connection between unmanned aerial vehicles (UAVs) and cellular networks in complex real-time channel state, and reduce the energy consumption of UAV during flight mission, an online trajectory optimization scheme of UAV based on outage probability knowledge map reconstruction is proposed. The outage probability knowledge map is a database that simulates the connection between UAV and the cellular network during real hovers. The UAV first samples sparsely from the target area and calculates the outage probability of the sampling point, and then uses the Kriging algorithm to reconstruct the outage probability knowledge map. Based on the reconstructed outage probability knowledge map, with the goal of minimizing the energy consumption of UAV task execution, the UAV trajectory optimization problem is established, and a trajectory optimization algorithm based on deep reinforcement learning (DRL) is proposed to solve it. Numerical results show that the proposed online trajectory optimization scheme based on outage probability knowledge map can obtain great returns in terms of maintaining connectivity, reducing task completion time and energy consumption.

Specific emitter identification (SEI) plays an increasingly crucial and potential role in both military and civilian scenarios. It refers to a process to discriminate individual emitters from each other by analyzing extracted characteristics from given radio signals. Deep learning (DL) and deep neural networks (DNNs) can learn the hidden features of data and build the classifier automatically for decision making, which have been widely used in the SEI research. Considering the insufficiently labeled training samples and large-unlabeled training samples, the semi-supervised learning-based SEI (SS-SEI) methods have been proposed. However, there are few SS-SEI methods focusing on extracting the discriminative and generalized semantic features of radio signals. In this article, we propose an SS-SEI method using metric-adversarial training (MAT). Specifically, pseudo labels are innovatively introduced into metric learning to enable semi-supervised metric learning (SSML), and an objective function alternatively regularized by SSML and virtual adversarial training (VAT) is designed to extract discriminative and generalized semantic features of radio signals. The proposed MAT-based SS-SEI method is evaluated on an open-source large-scale real-world automatic-dependent surveillance–broadcast (ADS-B) data set and Wi-Fi data set and is compared with the state-of-the-art methods. The simulation results show that the proposed method achieves better identification performance than existing state-of-the-art methods. Specifically, when the ratio of the number of labeled training samples to the number of all training samples is 10%, the identification accuracy is 84.80% under the ADS-B data set and 80.70% under the Wi-Fi data set. Our code can be downloaded from https://github.com/lovelymimola/MAT-based-SS-SEI .

Radio frequency fingerprint (RFF), which comes from the imperfect hardware, is a potential feature to ensure the security of communication. With the development of deep learning (DL), DL-based RFF identification methods have made excellent and promising achievements. However, on one hand, existing DL-based methods require a large amount of samples for model training. On the other hand, the RFF identification method is generally less effective with limited amount of samples, while the auxiliary dataset and the target dataset often needs to have similar data distribution. To address the data-hungry problems in the absence of auxiliary datasets, in this paper, we propose a supervised contrastive learning (SCL)-based RFF identification method using data augmentation and virtual adversarial training (VAT), which is called “SCACNN”. First, we analyze the causes of RFF, and model the RFF identification problem with augmented dataset. A non-auxiliary data augmentation method is proposed to acquire an extended dataset, which consists of rotation, flipping, adding Gaussian noise, and shifting. Second, a novel similarity radio frequency fingerprinting encoder (SimRFE) is used to map the RFF signal to the feature coding space, which is based on the convolution, long-short-term-memory, and a fully connected deep neural network (CLDNN). Finally, several secondary classifiers are employed to identify the RFF feature coding. The simulation results show that the proposed SCACNN has greater identification ratio than the other classical RFF identification methods. Moreover, the identification ratio of the proposed SCACNN achieves an accuracy of 92.68% with only 5% samples.

The topic of anonymous unmanned aerial vehicle (UAV) localizing based on angle estimation has been frequently discussed in the past few years. However, the existing methodologies are inefficient in a massive sensor arrays scenario. To avoid such drawback, a cooperative 3-D positioning methodology is introduced. The critical idea of the proposed localizing method is to estimate the 2-D angle of the anonymous UAV via a polarized massive–multi-input multi-output (MIMO) system. To reduce the computational burden and explore the nature of the multidimensional data, a tensor compressive sampling (TCS) framework is proposed. Moreover, a closed-form estimation strategy is developed for 2-D direction finding. Our framework is shown to be more efficient than the existing algorithm in terms of hardware/software complexity. Besides, it is suitable for a polarized MIMO system with an arbitrary array geometry. Several simulation examples are provided to show its improvement of the new methodology.

Joint transmit-receive diversity (JTRD) is expected to significantly improve the transmission performance in a multi-input multi-output (MIMO) fading channel. In practical situations, the number of base station (BS) antennas is much larger than that of user equipment (UE) antennas, resulting in an asymmetric MIMO fading channel. In this paper, a practical user-driven suboptimal JTRD scheme assuming time division duplex (TDD) in such an asymmetric MIMO fading channel is investigated. In a user-driven suboptimal JTRD scheme, firstly the user equipment (UE) determines its diversity weight vector, and then, BS determines its diversity weight vector so as to maximize the resulting composite channel gain for the given UE diversity weight vector. While the optimal JTRD jointly optimizes the diversity weight vectors at BS and UE by solving the eigen-equations composed of MIMO channel matrix. In principle, the user-driven suboptimal JTRD provides lower diversity gain than the optimal JTRD. In this paper, it is shown by numerical link capacity evaluation that in an asymmetric MIMO fading channel, where the number of BS antennas is much larger than that of UE antennas, the use of selection diversity in user-driven suboptimal diversity provides a slightly higher diversity gain than the use of maximal-ratio diversity and that the link capacity gap between the user-driven suboptimal JTRD and the optimal JTRD becomes quite small.

In 5G and beyond 5G systems, ultra-densification of radio access network (RAN) to improve the spectrum utilization efficiency is necessary due to continuously increasing mobile data traffic volume. Simple ultra-densification of RAN is not desirable since the problems of frequent handoff and severe interference will be caused. It is desirable to build the ultra-dense RAN based on the distributed multi-user multi-input multi-output (MU-MIMO) technology. In this paper, the design concept of cellular distributed MU-MIMO is presented to realize scalable ultra-dense RAN. In cellular distributed MU-MIMO, a wide communication service area is divided into a number of disjointed areas called cells using the distributed antenna location information and then, multiple user-centric small cells called user-clusters are formed in each cell using the user location information. To effectively mitigate intra- and inter-cell interferences caused by RAN ultra-densification, fully and semi-decentralized interference coordination (IC) schemes are presented.

Cell-free massive multiple-input multiple-output (CF-mMIMO) systems have been attracting a great attention as a promising architecture for the beyond fifth-generation (B5G) systems. CF-mMIMO is designed to deploy a large number of base station (BS) antennas to accommodate a relatively small number of mobile users. Considering that the computational complexity and the fronthaul capacity are limited in any practical system, scalability is the key to making CF-mMIMO practical. Thus, a user-centric (UC) approach is taken, i.e., each user is served by a certain number of antennas with high channel gain (called the antenna-set). Such a CF-mMIMO is called UC CF-mMIMO in this paper. However, as the user density becomes higher, the antenna-sets tend to overlap at a higher probability, and accordingly, severer interference will occur among the neighborhood users, thereby degrading the transmission performance of UC CF-mMIMO. To mitigate this severer interference problem, in this paper, we propose to group the neighborhood users as the user-cluster and to apply multi-user MIMO (MU-MIMO) technology to each user-cluster. This CF-mMIMO is called cluster-centric (CC) CF-mMIMO. In CC CF-mMIMO, user-clusters are first formed and a set of antennas is associated with each user-cluster for performing MU-MIMO communication in parallel. We evaluate the link capacity and the user fairness by computer simulation to reveal that the proposed CC CF-mMIMO outperforms the UC CF-mMIMO.

Radio frequency-based device-free passive perception (RF-DFPP) is considered as one of the most promising techniques for ubiquitous smart applications in the WiFi field due to its extremely low deployment cost. Existing RF-DFPP methods typically employ received signal strength indicator (RSSI), ignoring the potential benefits of fine-grained sensing accuracy of channel state information (CSI). In addition, the robustness of such sensing methods is not good at present. To solve the problem, in this paper, we propose a robust CSI-based RF-DFPP method using a combination network of convolutional neural networks (CNN) and attention-based bi-directional long short term memory (LSTM). The combined network can extract the signal features of the collected CSI through CNN, and then realize RF-DFPP recognition through the training of LSTM and attention layers. Simulation results show that the proposed method significantly improves the recognition accuracy compared with the existing methods. Moreover, it performs robustly even if the model training is done under the different datasets.

Due to the computing capability and memory limitations, it is difficult to apply the traditional deep learning (DL) models to the edge devices (EDs) for realizing automatic modulation classification (AMC). In this paper, a lightweight neural network for decentralized learning-based automatic modulation classification (DecentAMC) method is proposed. Specifically, group convolutional neural network (GCNN) is designed by replacing the standard convolution layer with the group convolution layer, replacing the flatten layer with the global average pooling (GAP) layer and removing part of fully connected layers. DecentAMC method is achieved by the cooperation in which multiple EDs update and upload the model weight to a central device (CD) for model aggregation to avoid the data privacy disclosure. Experimental results show that the proposed GCNN-based DecentAMC method can improve training efficiency to about 4 times and 57 times than that of GCNN-based centralized AMC (CentAMC) and CNN-based DecentAMC respectively. GCNN-based DecentAMC method can effectively reduce the communication cost and save storage of EDs when compared with CNN-based DecentAMC. Meanwhile, the time complexity and the space complexity of GCNN is significantly decreased when compared with CNN and SCNN, which is suitable to be deployed in EDs.

Optimal joint transmit-receive diversity (JTRD) is a multi-input multi-output (MIMO) spatial diversity technique and is designed to maximize the composite channel gain. A set of optimal JTRD weight vectors is a solution of eigen-equations or is derived by applying the singular value decomposition of MIMO channel. In this paper, instead of solving eigen-equations, a recursive solution method for obtaining the optimal JTRD weight vectors is proposed. Also proposed is the JTRD weight vectors sharing between base station (BS) and user, which makes it possible that either of BS or user carries out the recursive solution method. It is confirmed by computer simulation assuming a single-user Rayleigh faded MIMO channel that the proposed recursive solution method can obtain the JTRD weight vectors by only about 3-5 times updating and can achieve the channel capacity almost identical to the optimal JTRD.

Specific emitter identification (SEI) is developed as a potential technology against attackers in cognitive radio networks and authenticate devices in Internet of Things (IoT). It refers to a process to discriminate individual emitters from each other by analyzing extracted characteristics from given radio signals. Due to the strong capability of deep learning (DL) in extracting the hidden features of data and making classification decision, deep neural networks (DNNs) have been widely used in the SEI. Considering the insufficiently labeled training dataset and large unlabeled training dataset, we propose a novel SEI method using semi-supervised (SS) learning framework, i.e., metric-adversarial training (MAT). Specifically, two object functions (i.e., cross-entropy (CE) loss combined with deep metric learning (DML) and CE loss combined with virtual adversarial training (VAT)) and an alternating optimization way are designed to extract discriminative and generalized semantic features of radio signals. The proposed MAT-based SS-SEI method is evaluated on an open source large-scale real-world automatic-dependent surveillance-broadcast (ADS-B) dataset. The simulation results show that the proposed method achieves a better identification performance than four latest SS-SEI methods.

To address the problem of spectrum resources and transmitting power for vehicular networks, this paper proposes a resource allocation (RA) method based on dueling double deep-Q network (D3QN) reinforcement learning (RL). Due to the high mobility of the vehicle, the channel changes rapidly which makes it difficult to accurately collect high-accuracy channel state information at the base station and to perform centralized management. In response of this difficulty, we construct a multi-intelligence model, using Manhattan Grid Layout City Model as the basis of environment and with each vehicle-to-vehicle (V2V) link as an intelligence. They work together to interact with the environment, receive appropriate observations, get rewards, and finally learn to improve the allocation of power and spectrum to enable users to achieve a better entertainment experience and a safer driving environment. Experimental results demonstrate that with proper training mechanism and reward function construction, cooperation among multiple intelligence can be performed in a distributed manner, with improvements in both the capacity of total vehicle-to-infrastructure links and the effective payload delivery success rate of the V2V links compared to common Q-network.

In this paper, we propose a concept of a scalable and reconfigurable distributed multiuser MIMO (MU-MIMO) system and an interference coordination for ultra-dense radio access network (RAN). With careful consideration of the feasible radio signal processing capability for MU-MIMO, the communication service area is divided into a number of disjointed small areas (cells), each being formed based on the distributed antenna location information, and then, users in each cell are grouped into multiple user-clusters based on the user location information. In order to improve the spectrum efficiency, small-scale cluster-wise distributed MU-MIMO signal transmission is performed in parallel by reusing the same frequency in all user-clusters in all cells. However, in return, the strong interference is produced and this limits the improvement of system capacity. Hence, the introduction of interference coordination is essential. We evaluate the user capacity by computer simulation to show the effectiveness of the proposed scalable and reconfigurable distributed MU-MIMO system and interference coordination.

To ensure system scalability and to mitigate inter-user interference in cell-free massive MIMO (CF-mMIMO), a user-centric (UC) antenna-clustering approach was investigated. In this UC approach, user-centric antenna-clusters are formed by selecting cooperating antennas for each user, and postcoding is applied by regarding users whose antenna-clusters overlap as interfering users. However, in very high user density environments, since the number of interfering users increases due to increased overlapping of antenna-clusters, the achievable link capacity may degrade. In this paper, we propose a user-cluster-centric (UCC) approach, which groups neighborhood users into a user-cluster and associates the predetermined number of antennas to the user cluster for spatial multiplexing. We evaluate, by computer simulation, the uplink capacity of UCC CF-mMIMO using zero-forcing (ZF) and minimum mean square error (MMSE) based postcoding. We confirm that the proposed UCC approach can provide higher link capacity in a high user density environment.

Specific emitter identification (SEI) is a highly potential technology for physical-layer authentication that is one of the most critical supplements for the upper-layer authentication. SEI is based on radio frequency (RF) features from circuit difference, rather than cryptography. These features are inherent characteristics of hardware circuits, which are difficult to counterfeit. Recently, various deep learning (DL)-based conventional SEI methods have been proposed, and achieved advanced performances. However, these methods are proposed for close-set scenarios with massive RF signal samples for training, and they generally have poor performance under the condition of limited training samples. Thus, we focus on few-shot SEI (FS-SEI) for aircraft identification via automatic dependent surveillance-broadcast (ADS-B) signals, and a novel FS-SEI method is proposed, based on deep metric ensemble learning (DMEL). Specifically, the proposed method consists of feature embedding and classification. The former is based on metric learning with a complex-valued convolutional neural network (CVCNN) for extracting discriminative features with compact intracategory distance and separable intercategory distance, while the latter is realized by an ensemble classifier. Simulation results show that if the number of samples per category is more than 5, the average accuracy of our proposed method is higher than 98%. Moreover, feature visualization demonstrates the advantages of our proposed method in both discriminability and generalization. The code and the dataset can be downloaded fromhttps://github.com/BeechburgPieStar/FS-SEI.

Enabling ultrareliable low-latency communication (URLLC) with stringent requirements for transmitting data packets (e.g., 99.999% reliability and 1-ms latency) presents considerable uplink transmission challenges. For each packet transmission over dynamically allocated network radio resources, the conventional random access protocols are based on a request-grant scheme. This induces excessive latency and necessitates reliable control signaling, resulting in overhead. To address these problems, grant-free (GF) solutions are proposed in the fifth-generation (5G) new radio (NR). In this article, an overview and vision of the state of the art in enabling GF URLLC are presented. In particular, we first provide a comprehensive review of NR specifications and techniques for URLLC, discuss underlying principles, and highlight impeding issues of enabling GF URLLC. Furthermore, we briefly explain two key phenomena of massive multiple-input–multiple-output (mMIMO) (i.e., channel hardening and favorable propagation) and build several deep insights into how celebrated mMIMO features can be exploited to address the issues and enhance the performance of GF URLLC. Moving further ahead, we examine the potential of cell-free (CF) mMIMO and analyze its distinctive features and benefits over mMIMO to resolve GF URLLC issues. Finally, we identify future research directions and challenges in enabling GF URLLC with CF mMIMO.

Malware traffic classification (MTC) is a key technology for anomaly and intrusion detection in secure Industrial Internet of Things (IIoT). Traditional MTC methods based on port, payload, and statistic depend on the manual-designed features, which have low accuracy. Recently, deep-learning methods have attracted a significant attention due to their high accuracy in terms of classification. However, in practical application scenarios, deep-learning methods require a large amount of labeled samples for training, while the available labeled samples for training are very rare. Furthermore, the preparation of a large amount of labeled samples requires a lot of labor costs. To solve these problems, this article proposes three methods based on semisupervised learning (SSL), transfer learning (TL), and domain adaptive (DA), respectively. Our proposed methods use a large amount of unlabeled data collected in the Internet traffic, which can greatly improve the classification accuracy with few labeled samples. Then, we use the DA method to solve the mismatch problem between the source domain and the target domain in the TL process. The proposed method is not only applicable to the shallow network but also to the deep neural network structure, and can achieve better classification results. Experimental results show that our proposed methods can satisfy the requirement of MTC in the case of few labeled samples in IIoT. The source code for all the experiments is available at GitHub.The code of this article can be downloaded from GitHub link:https://github.com/yzjh/Keras-MTC-DA-Ladder.

Energy-efficiency (EE) is a critical metric within wireless optimization. Power control over fading channels is considered as a promising EE-improving technique, but requires optimization of a series of fractional functional optimization problems which are hard to handle by existing optimization techniques. In this paper, we propose a novel EE power control method with unsupervised learning. Firstly, the original fractional problems are decomposed into sub-problems by Dinkelbach and quadratic transformations. Then, these sub-problems are reformulated into unconstrained forms through Lagrange dual formulation. Furthermore, unsupervised primal-dual learning method is applied to handle these unconstrained problems with strong duality. Finally, The unsupervised primal-dual learning is implemented by the deep neural network (DNN) with low computational complexity. Simulation results verify the effectiveness of the proposed approach on a number of typical wireless optimizing scenarios. It is shown that compared to conventional algorithms our method achieves better performance in cognitive radio networks, interference networks, and OFDM networks.

Joint transmit-receive diversity (JTRD) is one of spatial diversity techniques to mitigate the communication quality degradation caused by multipath fading. In JTRD, the transmitter and the receiver cooperate so as to maximize the received signal-to-noise ratio (SNR). On the other hand, eigenmode beamforming (EMBF) technique is known to improve the spectrum efficiency by transmitting multiple data streams. The transmitter and receiver weight matrices of EMBF consist of the right- and left-singular vectors, respectively. In this paper, it is shown that optimal JTRD corresponds to the single-stream EMBF using the maximum singular value. In optimal JTRD, the achievable channel capacity improves as the fading correlation at the receiver becomes stronger. We try to understand such a behavior from a viewpoint of EMBF in correlated fading channels. By Monte-Carlo numerical computation assuming two-antenna receiver case, such a behavior of optimal JTRD is shown to result from the fact that as the fading correlation becomes stronger, the next maximum singular value (eigenvalue) fades rapidly and, in return, the maximum singular value (eigenvalue) becomes stronger.

The ultra-dense radio access network with large number of distributed antennas has been regarded as a promising technique for 5G advanced systems. However, the prohibitively large computational complexity limits its application in reality. In our previous researches, we proposed to form the users/antennas clusters to reduce the computational complexity, but as a side effect, the inter-cluster interference is also produced. The inter-cluster interference together with the inter-cell interference, which exist originally in macro cell cellular system, greatly affect the further improvement in link capacity. In this paper, we propose a graph coloring based-interference coordination in order to mitigate the inter-cluster interference and inter-cell interference cooperatively. The computer simulation confirms that our proposed algorithm can achieve an average 30% increase in sum link capacity compared with the 1-color case (i.e., single frequency reuse), and as high as the 94% of the upper limit.

Massive MIMO beamforming is an essential technique for 5G and beyond 5G systems. In this paper, we try to give a theoretical foundation to the massive MIMO beamforming from the principle of a multi-user joint transmit-receive diversity (JTRD). Multi-user JTRD is designed to maximize each user's composite MIMO channel gain. It is shown that multi-user JTRD using linear array at a base station (BS) is equivalent to full/hybrid beamforming. The received signal-to-noise ratio (SNR) expression is derived for a given multi-user MIMO channel. Then, the 2-user link capacity in a Rayleigh fading environment is evaluated by Monte-Carlo numerical computation method.

Multiuser joint transmit-receive diversity (JTRD) utilizing spatially separated multiple antennas at transmitter and receiver is able to jointly perform multiuser multiplexing and spatial diversity in a multipath fading environment. A pair of JTRD weight vectors associated with each user is a solution of eigenvalue equations constructed of each user's multi-input multi-output (MIMO) channel matrix. Although the base station (BS) has sufficient space to equip multiple antennas, user's antennas are close to each other due to limited available space and thereby, they experience correlated fading. In this paper, we evaluate the achievable link capacity of multiuser JTRD in correlated Rayleigh fading channels. It is shown that the fading correlation does not always have a negative impact.

Millimeter wave (mmWave) and massive multiple input multiple output (MIMO) are recognized as key technologies in the forthcoming beyond the fifth-generation (B5G) and the sixth-generation (6G) wireless networks. In this paper, a multibeam MIMO non-orthogonal multiple access (NOMA) scheme with weighted beam superposition for mmWave is proposed to enhance the system sum rate while ensuring fairness of users as much as possible. Specifically, a method of power allocation is adopted to guarantee the minimum demanded for the quality of service (QoS) of the weak users (lower channel gain)in each group. Furthermore, to improve further the sum rate after the QoS of the weak users is satisfied, the coefficient of strong users' beam gain are set to the largest value. In system simulations, we compare the performance of three multi-beam schemes, i.e, beam splitting, beam superposition and the proposed scheme, together with a single beam scheme, and a TDMA scheme at different levels of the SNR. The simulation results demonstrate that the system sum rate of the proposed method is much higher than TDMA scheme and competitive compared to the best scheme.

Ultra-densification of radio access network (RAN) is essential to efficiently handle ever-increasing mobile data traffic. In ultra-dense RAN consisting of a large number of distributed antennas and users, the computational complexity of large-scale multi-user MIMO (MU-MIMO) becomes prohibitively high. To solve this complexity problem, users can be grouped into several clusters and cluster-wise MU-MIMO is carried out using the same radio resource simultaneously. However, strong inter-cluster interference is produced. Furthermore, distributed radio resource management (RRM) is desirable to make possible highly scalable and flexible deployment of ultra-dense RAN. However, in return, inter-cell interference is produced. Recently, in order to mitigate these interferences, the authors presented the concept of enhanced interference coordination (eIC) for ultra-dense RAN. In this paper, we describe the eIC using multi-layered user clustering and evaluate the user capacity, the sum capacity, and the fairness among users by computer simulation to show the effectiveness of the proposed eIC.

Cluster-wise distributed multi-user multiple-input multiple- output (MU-MIMO) is a promising solution for improving the system capacity and energy efficiency in the fifth generation (5G) advanced systems which accommodate much larger number of user equipments (UEs) and utilize higher frequency bands. Clustering method can be introduced to separate the large-scale MU-MIMO to several small ones to mitigate the problem of prohibitively high computational complexity. In return, the inter-cluster-interference is produced and degrades the capacity. To remedy this capacity degradation problem, the power allocation can be introduced. In this paper, we propose a power allocation strategy for sum capacity maximization. The proposed power allocation strategy is compared with equal power allocation (EPA) strategy. It is confirmed by the computer simulation that the proposed strategy is superior in terms of sum capacity.

This paper proposes a decentralized automatic modulation classification (DecentAMC) method using light network and model aggregation. Specifically, the lightweight network is designed by separable convolution neural network (S-CNN), in which the separable convolution layer is utilized to replace the standard convolution layer and most of the fully connected layers are cut off, the model aggregation is realized by a central device (CD) for edge device (ED) model weights aggregation and multiple EDs for ED model training. Simulation results show that the model complexity of S-CNN is decreased by about 94% while the average CCP is degraded by less than 1% when compared with CNN and that the proposed AMC method improves the training efficiency when compared with the centralized AMC (CentAMC) using S-CNN.

Accurate channel state information (CSI) is necessary for frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. Existing deep learning-based CSI feedback methods, e.g., CSI sensing and recovery neural network (CsiNet), designed based on an autoencoder architecture, achieves higher feedback accuracy and reconstruction speed. However, this network needs to be retrained due to different communication scenarios and channel conditions, which is costly in practical deployment. To solve this problem, this paper proposes a deep learning-based modular adaptive multiple-rate (MAMR) compression CSI feedback framework. Extra padding modules are added at the base station to pad compressed CSI into different compression rates into the same dimensions, thereby realizing a general autoencoder performing variable-rate compression. Simulation results are given to confirm the effectiveness of the proposed method in terms of normalized mean square error.

Acquisition of downlink channel state information (CSI) is an important procedure performed at the base station (BS) for high quality wireless communication in frequency division duplexing (FDD) communication system. Generally, the downlink CSI is fed back to the BS through the user equipment (UE). Compared with traditional methods, neural network (NN) can effectively compress the downlink CSI, thus greatly reducing the feedback overhead. However, the generalization of the NN is poor, hence it is necessary to train a NN from scratch whenever there is a change in the wireless channel environment. Nevertheless, training a NN this way requires huge data and time cost in 5G massive MIMO systems. In this paper, deep transfer learning (DTL) is proposed to solve the problem of high training cost of the downlink CSI feedback NN. In a new wireless environment, our proposed technique utilises relatively small number of samples to fine-tune a pre-trained model, in order to obtain a new model with low training cost. The performance of this model is shown to be comparable with that of the NN trained with large samples. Experiment results demonstrate the effectiveness and superiority of the proposed method.

Nonorthogonal multiple access (NOMA) significantly improves the connectivity opportunities and enhances the spectrum efficiency (SE) in the fifth generation and beyond (B5G) wireless communications. Meanwhile, emerging B5G services demand for higher SE in the NOMA-based wireless communications. However, traditional ground-to-ground (G2G) communications are hard to satisfy these demands, especially for the cellular uplinks. To solve these challenges, this article proposes a multiple unmanned-aerial-vehicles (UAVs)-aided uplink NOMA method. In detail, multiple hovering UAVs relay data for a half of ground users (GUs) and share the spectrums with the other GUs that communicate with the base station (BS) directly. Furthermore, this article proposes a K-means clustering-based UAV deployment scheme and location-based user pairing (UP) scheme to optimize the transceiver association for the multiple UAVs-aided NOMA uplinks. Finally, a sum power minimization-based resource allocation problem is formulated with the lowest Quality-of-Service (QoS) constraints. We solve it with the message-passing algorithm and evaluate the superior performances of the proposed scheduling and paring schemes on SE and energy efficiency (EE). Extensive simulations are conducted to compare the performances of the proposed schemes with those of the single UAV-aided NOMA uplinks, G2G-based NOMA uplinks, and the proposed multiple UAVs-aided uplinks with a facility location framework-based UAV deployment. Simulation results demonstrate that the proposed multiple UAVs deployment and UP-based NOMA scheme significantly improves the EE and the SE of the cellular uplinks at the cost of only a little relaying power consumption of UAVs.

This paper proposes an unmanned aerial vehicle (UAV)-aided full-duplex non-orthogonal multiple access (FD-NOMA) method to improve spectrum efficiency. Here, UAV is utilized to partially relay uplink data and achieve channel differentiation. Successive interference cancellation algorithm is used to eliminate the interference from different directions in FD-NOMA systems. Firstly, a joint optimization problem is formulated for the uplink and downlink resource allocation of transceivers and UAV relay. The receiver determination is performed using an access-priority method. Based on the results of the receiver determination, the initial power of ground users (GUs), UAV, and base station is calculated. According to the minimum sum of the uplink transmission power, the Hungarian algorithm is utilized to pair the users. Secondly, the subchannels are assigned to the paired GUs and the UAV by a message-passing algorithm. Finally, the transmission power of the GUs and the UAV is jointly fine-tuned using the proposed access control methods. Simulation results confirm that the proposed method achieves higher performance than state-of-the-art orthogonal frequency division multiple-access method in terms of spectrum efficiency, energy efficiency, and access ratio of the ground users.

Automatic modulation classification (AMC) is a critical algorithm for the identification of modulation types so as to enable more accurate demodulation in the non-cooperative scenarios. Deep learning (DL)-based AMC is believed as one of the most promising methods with great classification accuracy. However, the conventional CNN-based methods are lack of generality capabilities under time-varying signal-to-noise ratio (SNR) conditions, because these methods are merely trained on specific datasets and can only work under the corresponding condition. In this paper, a novel multi-task learning (MTL)-based generalized AMC method is proposed, and a more realistic scenario is considered, including white non-Gaussian noise and synchronization error. Its generalization capability stems from knowledge-sharing-based MTL in varying noise scenarios. In detail, multiple CNN models with the same structure are trained for multiple SNR conditions, but they share their knowledge (e.g. model weight) with each other. Thus, MTL can extract the general features from datasets in different noise scenarios. Simulation results show that our proposed architecture can achieve higher robustness and generalization than the conventional ones.

Cyclically shifted partial transmit sequences (CS-PTS) has conventionally been used in SISO systems for PAPR reduction of OFDM signals. Compared to other techniques, CS-PTS attains superior performance. Nevertheless, due to the exhaustive search requirement, it demands excessive computational complexity. In this paper, we adapt CS-PTS to operate in a MIMO framework, where singular value decomposition (SVD) precoding is employed. We also propose SWAN, a novel optimization method based on swarm intelligence to circumvent the exhaustive search. SWAN not only provides a significant reduction in computational complexity, but it also attains a fair balance between optimality and complexity. Through simulations, we show that SWAN achieves near-optimal performance at a much lower complexity than other competing approaches.

In this paper, a multi-user MIMO using zeroforcing (ZF)-based multiplexing coordinated with user-wise spatial diversity is proposed assuming time-division duplex (TDD). The downlink and uplink signal-to-noise ratios (SNRs) are analyzed for the given multi-user MIMO channel. It is shown that the downlink capacity is the same for all users while the uplink capacity is not necessarily the same. The closed-form expressions for the downlink and uplink SNRs conditioned on the 2-user virtual MIMO channel are derived. It is shown that the uplink sum capacity is higher than the downlink sum capacity. The downlink and uplink capacities are numerically evaluated by Monte Carlo simulation in a Rayleigh fading environment. It is shown that the link capacity can be improved by increasing the number of user antennas while keeping the ZF matrix size in the same level.

Ultra-densification of radio access network (RAN) is necessary to handle ever-increasing mobile data traffic even after starting of 5G services. Dense reuse of the same radio resource produces severe interference. Furthermore, when extremely high frequency band like mmWave band is utilized, the radio link may be frequently blocked by obstacles placed between transmitter and receiver according to user movement. To realize highly reliable communications in such a severe radio link environment, an enhanced interference coordination (eIC) and radio resource management (RRM) needs to be introduced. In this paper, we will present the concept of an eIC and RRM for 5G advanced ultra-dense RAN using distributed MIMO, which integrates a classification of user-equipments (UEs) into inner-cell and cell-edge groups, UE clustering, cluster-antenna association, distributed MIMO cooperative transmission & reception (CTR), and scheduling. Then, we will present some preliminary results obtained by numerical computation.

Sparse code multiple access (SCMA) is an attractive non-orthogonal multiple access scheme for wireless communications. Meanwhile, space-time block coding (STBC) can achieve high diversity gains in fading channels. This paper proposes an uplink SCMA-STBC with a space-time-based message-passing algorithm (ST-MPA). Moreover, precoding is employed in the proposed SCMA-STBC to reduce the complexity of the receiver. The BER lower bound is derived for the proposed system. Simulation results show that the system with precoding provides a better BER performance than the case without precoding.

In ultra-dense RAN consisting of a large number of distributed antennas, the coverage and the capacity can be improved by forming a number of user clusters (also called virtual small cells) with each cluster consisting of neighbor users and by executing cluster-wise small-scale MIMO in parallel using the same radio resource. However, a straightforward clustering produces a severe inter-cluster interference (ICI) and the capacity improvement is much smaller than expected. In this paper, we propose a joint multilayered user clustering and scheduling. This approach is based on user clustering using the user location information, user-cluster layering based on the interference-offset-distance (IOD), antenna assignment on each layer, simple layer-by-layer round-robin-type scheduling and cluster-wise MIMO. We evaluate by computer simulation the user capacity, the sum capacity, and the fairness to show the effectiveness of the proposed joint multilayered user clustering and scheduling.

In this paper, we propose a convolutional neural network (CNN) aided automatic modulation recognition (AMR) method for a multiple antenna system. We also present two specific combination strategies, such as the relative majority voting method and arithmetic mean method to improve the classification performance in comparison with the state of the art. Our results are given to verify that the proposed method dominant exploits features and classify the modulation types with higher accuracy in comparison with the AMR employing high order cumulants (HOC) and artificial neural networks (ANN).

We started a new research project in the “advanced 5G” era that aims at accommodating various types of communications involving current and emerging services with different data flow-level quality requirements. In this paper, the objectives and the technical aspects of the research project are introduced. We propose an architecture based on a virtualized radio access network (vRAN) that enables adaptive control of equipment resources and location of functions in the vRAN environment in accordance with spatially and temporally changing communication demands. The seven planned research items that are essential for realizing the advanced 5G network are listed as follows: blockage prediction, new radio access technologies (RATs) and their implementations with software-defined radio (SDR), adaptive interference and resource control, integration of radio and fiber resource control, highly efficient access transmission control, adaptive placement of BS functions, and quality aware traffic pattern prediction.

Unmanned aerial vehicles (UAVs) are playing an important role in wireless networks, due to their cost effectiveness and flexible deployment. Particularly, integrating UAVs into existing cellular networks has great potential to provide high-rate and ultra-reliable communications. In this paper, we investigate the uplink transmission in a cellular network from a UAV using non-orthogonal multiple access (NOMA) and from ground users to base stations (BSs). Specifically, we aim to maximize the sum rate of uplink from UAV to BSs in a specific band as well as from the UAV's co-channel users to their associated BSs via optimizing the precoding vectors at the multi-antenna UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the UAV-connected BSs, but also to the BSs associated with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the transmission rate requirements is formulated, which is non-convex. Thus, we introduce auxiliary variables and apply approximations based on the first-order Taylor expansion to convert it into a second-order cone programming. Accordingly, an iterative algorithm is designed to obtain the solution to the problem with low complexity. Numerical results are presented to demonstrate the effectiveness of our proposed scheme.

The increasing demands for massive connectivity, low latency, and high reliability of future communication networks require new techniques. Multiple-input-multiple-output non-orthogonal multiple access (MIMO-NOMA), which incorporates the NOMA concept into MIMO, is an appealing technology to enhance system throughput and energy efficiency. However, rapidly changing channel conditions and extremely complex spatial structure degrade the system performance and hinder its application. Thus, to tackle these limitations, in this paper, we propose a deep learning-based MIMO-NOMA framework for maximizing the sum data rate and energy efficiency. To be specific, we design an effective communication deep neural network (CDNN) in which several convolutional layers and multiple hidden layers are included. Thanks to the impressive representation ability of the deep learning technique, the CDNN framework addresses the power allocation problem for achieving higher data rate and energy efficiency of MIMO-NOMA with the aid of training algorithms. Additionally, simulation results corroborate that the proposed CDNN framework is a good candidate to enhance the performance of MIMO-NOMA in term of power allocation, and extensive simulations show that it realizes larger sum data rate and energy efficiency compared with conventional strategies.

Hybrid analog-digital precoding is challenging for broadband millimeter-wave (mmWave) massive MIMO systems, since the analog precoder is frequency-flat but the mmWave channels are frequency-selective. In this paper, we propose a principal component analysis (PCA)-based broadband hybrid precoder/combiner design, where both the fully-connected array and partially-connected subarray (including the fixed and adaptive subarrays) are investigated. Specifically, we first design the hybrid precoder/combiner for fully-connected array and fixed subarray based on PCA, whereby a low-dimensional frequency-flat precoder/combiner is acquired based on the optimal high-dimensional frequency-selective precoder/combiner. Meanwhile, the near-optimality of our proposed PCA approach is theoretically proven. Moreover, for the adaptive subarray, a low-complexity shared agglomerative hierarchical clustering algorithm is proposed to group the antennas for the further improvement of spectral efficiency (SE) performance. Besides, we theoretically prove that the proposed antenna grouping algorithm is only determined by the slow time-varying channel parameters in the large antenna limit. Simulation results demonstrate the superiority of the proposed solution over state-of-the-art schemes in SE, energy efficiency (EE), bit-error-rate performance, and the robustness to time-varying channels. Our work reveals that the EE advantage of adaptive subarray over fully-connected array is obvious for both active and passive antennas, but the EE advantage of fixed subarray only holds for passive antennas.

Distributed multiple-input multiple-output (MIMO) is a type of the centralized radio access network (C-RAN) to achieve a high link capacity uniformly over the service area. A large-scale distributed MIMO requires prohibitively high computational complexity. Clustering of user equipments (UEs) can reduce the computational complexity, however, this produces the inter-cluster interference (ICI). In this paper, we propose the UE clustering and antenna selection beyond the cluster boundary assuming multi-user minimum mean square error filtering combined with singular value decomposition (MMSE-SVD). We exploit the multiplexing-diversity tradeoff in MMSE-SVD to suppress effectively the ICI while keeping the multi-user multiplexing capability. It is shown that the proposed UE clustering and antenna selection can achieve 6 times higher sum capacity and 1.6 times higher UE capacity, compared to the without clustering.

In this paper, channel tracking in fast-varying MIMO environments is considered. Firstly, the high-dimension channel vector of each user is decomposed into a semi-static factor load matrix (FLM) and a low-dimension factor coefficient vector (FCV). Thereby, channel tracking is replaced by the infrequent FLM tracking and low-complexity FCV tracking. Secondly, channel variations are represented by local polynomial modeling, based on which a recursive least square (RLS) algorithm with optimal forgetting factor (FF) is proposed. It is verified that the proposed algorithm has higher accuracy, better tracking ability and lower computational complexity than the existing methods.

In this paper, we investigate the uplink transmission in a cellular network from a UAV and ground users to ground base stations (BSs). Specifically, we aim to maximize the sum rate of the uplink from the UAV to ground BSs in a specific idle frequency band as well as from the co-channel users to their associated BSs by optimizing precoding vectors at UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the BSs connected with UAV using non-orthogonal multiple access (NOMA) for transmission, but also to other BSs communicating with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the uplink transmission rate is formulated, which is non-convex and intractable. Thus, we introduce auxiliary variables and apply first-order approximations based on Taylor expansion to convert it into a second-order cone programming. An iterative algorithm is proposed with low complexity to calculate the solution to the non-convex precoding optimization problem. Numerical results demonstrate the effectiveness of our proposed scheme.

In this paper, we make a summary report of our 5G R&D activities for “High Capacity Technologies with Ultra High-Density Multi-Band and Multi-Access Layered Cells”, funded by the Ministry of Internal Affairs and Communications (MIC) in Japan. This national project consists of three research subjects: “Ultra high-density distributed antenna systems”, “Optical access technologies accommodating highly densified small cells” and “Multi-RAT system technologies for multi-band and multi-access layered cells”. We describe the research and development result for each subject.

When natural disasters strike, the coverage for Internet of Things (IoT) may be severely destroyed, due to the damaged communications infrastructure. Unmanned aerial vehicles (UAVs) can be exploited as flying base stations to provide emergency coverage for IoT, due to its mobility and flexibility. In this paper, we propose multiantenna transceiver design and multihop device-to-device (D2D) communication to guarantee the reliable transmission and extend the UAV coverage for IoT in disasters. First, multihop D2D links are established to extend the coverage of UAV emergency networks due to the constrained transmit power of the UAV. In particular, a shortest-path-routing algorithm is proposed to establish the D2D links rapidly with minimum nodes. The closed-form solutions for the number of hops and the outage probability are derived for the uplink and downlink. Second, the transceiver designs for the UAV uplink and downlink are studied to optimize the performance of UAV transmission. Due to the nonconvexity of the problem, they are first transformed into convex ones and then, low-complexity algorithms are proposed to solve them efficiently. Simulation results show the performance improvement in the throughput and outage probability by the proposed schemes for UAV wireless coverage of IoT in disasters.

Blind selected mapping (blind SLM) is an effective peak-to-average power ratio (PAPR) reduction technique which does not require side information sharing. In the blind SLM, the receiver employs phase rotation sequence estimation, which can be carried out using maximum-likelihood (ML) estimation or 2-step sequence estimation using Viterbi algorithm. ML estimation typically requires much higher computational complexity. Recently, we showed that the use of codebook generated from a 2-level phase rotation set {0°, 135°} and the ML phase rotation sequence estimation based on the fourth-power QAM constellation requires much less complexity compared to the conventional blind SLM with 3-level phase rotation set {0°, 120°, 240°} and ML estimation based on original QAM constellation. However, for a large number of phase rotation sequences, the computational complexity still remains high. In this paper, in order to further reduce the computational complexity, we propose a combined use of a 2-level phase rotation set {0°, 135°} and the 2-step sequence estimation. The use of 2-level phase rotation set significantly reduces the number of branches and states in the Viterbi algorithm and hence, leads to complexity reduction. Simulation results confirm that the blind SLM using the 2-level phase rotation set and the 2-step sequence estimation has less computational complexity while achieving similar BER to the ML sequence estimation.

Distributed multi-input multi-output (MIMO) provides a good transmission quality over a macro-cell area. However, the cell-edge user equipments (UEs) still suffer from strong inter-cell interference (ICI) from surrounding macro-cells and hence, their transmission quality degrades compared to the cell-center UEs. In order to mitigate the ICI problem, in this paper, we propose a de-centralized adaptive 2-step ICI coordination (ICIC) based on fractional frequency reuse (FFR). Adaptive 2-step ICIC consists of the UE classification into cell-center UEs and cell-edge UEs and the adaptive selection of fractional bands.

In this paper, the channel estimation (CE) scheme suitable for MIMO cooperative transmission using time division duplex (TDD) in a high mobility environment is considered. We propose a decision-feedback linear prediction (DF-LP) CE scheme, which is used during data transmission. The uncoded bit error rate (BER) performances of OFDM downlink using maximal ratio transmit diversity (MRTD) and single-carrier (SC) uplink using minimum mean square error combining diversity (MMSECD) are evaluated by computer simulation. It is confirmed that the proposed DF-LP CE scheme can significantly improve the BER performance in a very high mobility environment.

Blind selected mapping (blind SLM) is an effective peak-to-average power ratio (PAPR) reduction technique, in which the phase rotation sequence which has been used at the transmitter is blindly estimated. The Euclidean distance between the received symbols after de-mapping and the original QAM constellation is used for the estimation, which requires high computational complexity. In this paper, we introduce a phase rotation sequence estimation based on the minimum Euclidean distance of the fourth-power constellation. The use of fourth-power constellation reduces symbol candidates in minimum Euclidean distance calculation and hence, contributes to complexity reduction. A set of phase rotation sequences constructed by random selection from {0°, 135°} are also introduced to further reduce the complexity and maintain high estimation accuracy. Simulation result confirms that the proposed phase rotation and sequence estimation technique can reduce the complexity without degrading the uncoded bit error rate (BER) performance for the given PAPR reduction.

The requirement of the increasing capacity of the communication networks promotes the massive multiple input multiple output (MIMO), which has attracted a lot of attention among academic and industry communities. Due to the inherent sparsity features of channel structure in uplink massive MIMO systems, conventional methods often bring about high computational complexity and also fail to make full use of the structural information. In order to solve this problem, this paper proposes a novel deep learning (DL) based super-resolution direction of arrivals (DOA) estimation method. Specifically, it is realized with the aids of the well-designed deep neural network (DNN). Then we employ the DNN to carry out offline learning and online deployment procedures. This learning mechanism can learn the features of the wireless channel and the spacial structures efficiently. Finally, simulation results are provided to show that the proposed DL based scheme can achieve better performance in terms of the DOA estimation compared with conventional methods.

In this paper, we consider a relay assisted backscatter communication (RaBackCom) system, where a user backscatters incident signals from a carrier emitter (CE) to a relay and a receiver simultaneously, and then the relay forwards the user's information to the receiver for throughput improvement. We consider two cases that the relay is with/without an embedded energy source. Specifically, if the relay does not have an energy source, it first harvests energy from the signals from the CE and then uses its harvested energy for information forwarding. For both cases, we formulate time allocation problems on the user's information backscattering, the user's information forwarding, or the relay's energy harvesting to maximize the system throughput, and then derive closed-form solutions. Simulation results demonstrate the advantages of the proposed relay cooperation scheme with the optimal time allocation in terms of system throughput.

Multi-User Multiple Input Multiple Output (MU-MIMO) can significantly increase the link capacity without bandwidth expansion. One promising technique is MMSE-SVD, which is a combination of minimum mean square error (MMSE) filter at the base station (BS) side and eigenmode filter generated by singular value decomposition (SVD) at user equipment (UE) side. MMSE-SVD requires BS and UEs to share the MIMO channel state information (CSI) prior to data transmission. This may cause a serious problem in a high mobility environment; the shared MIMO CSI becomes outdated and consequently, the bit-error rate (BER) performance degrades. In this paper, we propose an adaptive MMSE-SVD, which updates the transmit filter using channel prediction and the receive filter using decision-feedback channel estimation. The uncoded BER performance of adaptive MMSE-SVD for orthogonal frequency division multiplexing (OFDM) downlink and single-carrier (SC) uplink is evaluated by computer simulation. Simulation results confirmed that adaptive MMSE-SVD increases the allowable maximum Doppler frequency ( fDT) for keeping by about 4 times for OFDM downlink while by about 1.6 times for SC uplink.

Our main aim is to develop and demonstrate energy saving technologies for mobile terminals (MTs) equipped with multiple wireless interfaces. We propose a new framework of device-to-device (D2D) cooperative virtual small-cell network in which a MT acts a virtual base station to take advantage of the good channel quality of long range link and the low energy consuming interface of short range link to save energy in MTs. In the proposed D2D cooperative virtual small-cell framework, how to select proxy MT which connects to the wide area network (WAN) and provides the local area network (LAN) connection to cooperated MTs is an important issue, and it is influenced by multiple factors such as channel quality both in WAN and LAN, throughput, battery lifetime, mobility of MTs. In this paper, the energy efficiency improvement is evaluated by a smartphone test-bed and the impacts of WAN channel condition and the number of cooperated MTs are discussed. The result shows that up to 66% improvement can be achieved by the proposal compared to the traditional systems without cooperation.

Channel feedback is essential for frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems to realize precoding and power allocation. Traditional codebooks for channel feedback, where the required number of feedback bits is proportional to the number of base station (BS) antennas, can not scale up with massive MIMO due to the large number of BS antennas. To solve this problem, in this paper, we propose an angle-of-departure (AoD) adaptive subspace codebook to reduce the codebook size and feedback overhead. Specifically, by leveraging the concept of angle coherence time, which implies that the path AoDs vary much slower than path gains, we propose an AoD-adaptive subspace codebook to quantize the channel vector in a more accurate way. We also provide performance analysis of the proposed AoD-adaptive subspace codebook, where we prove that the required number of feedback bits only scales linearly with the number of resolvable AoDs, which is much smaller than the number of BS antennas. This quantitative result is also verified by simulations.

We have been studying cooperative distributed antenna transmission (CDAT) as a promising technique for realizing the 5thgeneration (5G) high-speed mobile communications. Assuming time division duplex (TDD), the macro-cell base station (MBS) and the user equipments (UEs) conduct the channel estimation independently to obtain the shared channel state information (CSI). In this paper, we introduce a TDD frame structure consisting of uplink pilot time slot and downlink pilot time slot followed by data time slots. MIMO channel estimation is done before the user data transmission. Also presented is the pilot signal design. The accuracy of the proposed MIMO channel estimation and achievable bit error rate (BER) performance of user data transmission are evaluated by computer simulation.

Blind selected mapping (blind SLM) can effectively reduce the peak-to-average power ratio (PAPR) of both orthogonal frequency division multiplexing (OFDM) and single-carrier (SC) signals without side-information transmission. In typical blind SLM, maximum likelihood (ML) estimation is applied to find the de-mapping phase rotation sequence which gives the lowest Euclidean distance among all possible sequences, resulting in very high computational complexity. In this paper, we introduce a novel low-complexity 2-step estimation suitable for blind SLM. In the first step, the phase rotation sequence achieving the lowest Euclidean distance is searched by using the Viterbi algorithm. In the second step, verification and correction are carried out to choose a phase rotation sequence stored in the codebook, which has the lowest Hamming distance from the estimated sequence in the first step. It is confirmed by computer simulation that our proposed 2-step estimation achieves similar BER performance to the transmission without SLM and the transmission with blind SLM with the conventional ML estimation, but the proposed estimation technique requires much less complexity.

Distributed antenna small-cell network is a promising 5G network. In this paper, a comprehensive report of recent advance in the cooperative distributed antenna transmission (CDAT) is provided. Single-user space-time block coded transmit diversity (STBC-TD) and multi-user minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) are presented. Also presented is blind selected mapping (blind SLM) which can suppress the peak-to-average signal power ratio (PAPR) and requires no side information transmission. The effectiveness of CDAT in the presence of co-channel interference (CCI) from adjacent macro- cells is confirmed by computer simulation.

Cooperative distributed antenna transmission (CDAT) is a promising transmission technique to achieve a high link capacity by exploiting the spatial distribution of antennas over a macro-cell area. Recently, we proposed a minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) for multi-user spatial multiplexing and showed that it can achieve higher sum capacity with lower computational complexity than BD-SVD which applies SVD after block diagonalization (BD). When using multi-user scheduling, the link capacity of MU-MIMO is affected by the combination of spatially multiplexed user equipments (UEs). In this paper, we evaluate by computer simulation the OFDM downlink capacities of MMSE-SVD and BD-SVD considering three types of multi-user scheduling (Max-SNR, Proportional Fair (PF) and Round Robin (RR)). We show that the MMSE-SVD can achieve higher link capacity with higher fairness than BD-SVD.

The co-existence of small cell base stations (SBSs) with conventional macrocell base station is a promising approach to boost the capacity and coverage of cellular networks. However, densifying the network with a viral deployment of SBSs can significantly increase energy consumption. To reduce the reliance on unsustainable energy sources, one can adopt self-powered SBSs that rely solely on energy harvesting. Due to the uncertainty of energy arrival and the finite capacity of energy storage systems, self-powered SBSs must smartly optimize their ON and OFF schedule. In this paper, the problem of ON/OFF scheduling of self-powered SBSs is studied, in the presence of energy harvesting uncertainty with the goal of minimizing the operational costs consisting of energy consumption and transmission delay of a network. For the original problem, we show that an algorithm can solve the problem in the illustrative case. Then, to reduce the complexity of the original problem, an approximation is proposed. To solve the approximated problem, a novel approach based on the ski rental framework, a powerful online optimization tool, is proposed. Using this approach, each SBS can effectively decide on its ON/OFF schedule autonomously, without any prior information on future energy arrivals. By using competitive analysis, a deterministic online algorithm and a randomized online algorithm (ROA) are developed. The ROA is then shown to achieve the optimal competitive ratio in the approximation problem. Simulation results show that, compared with a baseline approach, the ROA can yield performance gains reaching up to 15.6% in terms of reduced total energy consumption of SBSs and up to 20.6% in terms of per-SBS network delay reduction. The results also shed light on the fundamental aspects that impact the ON time of SBSs while demonstrating that the proposed ROA can reduce up to 69.9% the total cost compared with a baseline approach.

Next generation mobile networks will face the unprecedented demand for higher data rates. To satisfy this demand, the dense deployment of heterogeneous wireless networks (HetNets) is a promising solution. One of the major challenges in dense HetNets is to dynamically allocate the resources such as power and channel so that the energy efficiency and throughput of the network improve. One of the important techniques for improving the energy efficiency of the base station (BS) is BS ON-OFF switching which allows the BS to turn off some of its components in lower load situations. On the other side, due to the proximity of BSs in the dense HetNets, co-channel interference (CCI) becomes a critical problem and significantly impacts the performance of the network. In this paper, we propose a dynamic channel assignment based on a learning algorithm (DCA-LA). Moreover, we combine DCA-LA with a BS ON-OFF switching algorithm in order to improve the energy efficiency of the system. In particular, the proposed DCA-LA/ON-OFF switching algorithm is self-organizing and performs in a fully distributed manner. Simulation results indicate that our proposed algorithm balances load among BSs and yields better performance in terms of average energy consumption, average load, average utility per BS and average rate per user, compared to the baseline algorithms.

The viral and dense deployment of small cell base stations (SBSs) will lie at the heart of 5G cellular networks. However, such dense networks can consume a significant amount of energy. In order to reduce the network's reliance on unsustainable energy sources, one can deploy self-powered SBSs that rely solely on energy harvesting. Due to the uncertainty of energy arrival and the finite capacity of energy storage systems, self-powered SBSs must smartly schedule their ON and OFF operation. In this paper, the problem of ON/OFF scheduling of self-powered SBSs is studied in the presence of energy harvesting uncertainty with the goal of minimizing the tradeoff between power consumption and flow-level delay. To solve this problem, a novel approach based on the ski rental framework, a powerful online optimization tool, is proposed. To find the desired solution of the ski rental problem, a randomized online algorithm is developed to enable each SBS to autonomously decide on its ON/OFF schedule, without knowing any prior information on future energy arrivals. Simulation results show that the proposed algorithm can reduce power consumption and delay over a given time period compared to a baseline that turns SBSs ON by using an energy threshold. The results show that this performance gain can reach up to 12.7% reduction of the total cost. The results also show that the proposed algorithm can eliminate up to 72.5% of the ON/OFF switching overhead compared to the baseline approach.

The deployment of heterogeneous networks (Het- Nets) is a promising candidate for the next-generation wireless networks. This is envisioned to deliver higher rate data services in flexible and cost-effective manner. However, in the HetNets, due to the coexistence of various nodes, traffic load variations are more pronounced which requires more dynamic resource management. On the other side, the effective management of resource can significantly impact on the experience of user equipment (UE) and network's performance. In this paper, we address a joint UE association (UEA) and downlink resource allocation problem in the HetNets. In this regard, we propose a UEA policy based on base stations' (BSs') estimated load and signal-to-interference-and-noise-ratio at the location of UE. Furthermore, we apply a self- organizing mechanism to allocate the resource for jointly optimizing the power and channel allocation in a fully distributed way. Our proposed joint UEA and self-organizing resource allocation balances load among BSs and improves the energy efficiency of the network. Simulation results show that our proposed joint UEA and resource allocation yields significant performance gains up to 26.4% and 22% compared to the other benchmark schemes in terms of average energy consumption and average BS load, respectively.

Single-carrier (SC) signal has a low peak-to-average power ratio (PAPR) property. However, the PAPR of SC signal increases if transmit filtering and/or high-level modulation are applied. We have recently proposed a time-domain selected mapping (TD-SLM) which effectively reduces the PAPR of filtered SC signals by applying the binary phase rotation before transmit filtering, but the necessity of side-information decreases the spectrum efficiency (SE). In this paper, a blind TD-SLM which does not require side-information is proposed. Unlike the frequency-domain SLM (FD-SLM) and the original TD-SLM with side-information, polyphase rotations are used. Performance evaluation of the proposed blind TD-SLM is done by computer simulation assuming turbo-coded filtered SC block signal transmission in aspects of PAPR and bit-error rate (BER) to show that no significant BER performance degradation is occurred.

Sparse adaptive filtering algorithms are utilized to exploit potential sparse structure information as well as to mitigate noises in many unknown sparse systems. Sparse recursive least square (RLS) algorithms have been attracted intensely attentions due to their low-complexity and easy- implementation. Basically, these algorithms are constructed by standard RLS algorithm and sparse penalty functions (e.g., l_1-norm). However, existing sparse RLS algorithms do not exploit the sparsity efficiently. In this paper, an improved adaptive filtering algorithm is proposed by incorporating a novel correntropy induced metric (CIM) constraint into RLS, which is termed as RLS- CIM algorithm. Specifically, we adopt a well-known Gaussian kernel in CIM and further devise a novel variable kernel width to control the sparse penalty in different transient-error scenarios. Numerical simulation results are given to corroborate the proposed algorithm via mean square deviation (MSD).

An introduction of multi-user multiple-input multiple-output (MU-MIMO) to distributed antenna-based small-cell networks is considered a promising approach toward 5G mobile networks to enhance the sum throughput. However, the inter-symbol interference (ISI) caused by the channel frequency-selectivity, the inter-antenna interference (IAI), and the inter-user interference (IUI) degrade the MU-MIMO downlink throughput. This paper proposes two joint transmit-and-receive (Tx/Rx) filtering schemes (called BD-SVD and MMSE-SVD) for MU-MIMO downlinks using single-carrier (SC) transmission and orthogonal frequency-division multiplexing (OFDM) transmission. In BD-SVD, IUI is removed by block diagonalization (BD) at the transmitter side, and then, the equivalent channel after BD is transformed into IAI-free eigenmodes using singular value decomposition (SVD). On the other hand, in MMSE-SVD, BD is not used and the channel is directly transformed into eigenmodes. IUI and IAI are suppressed by a minimum mean square error (MMSE)-based precoding at the transmitter assuming that each receiver does eigenmode reception. Furthermore, in the case of SC downlink, ISI is suppressed by applying MMSE-based Tx power allocation (PA) and Rx frequency-domain equalization (FDE) to each eigenmode. Numerical results show that BD-SVD and MMSE-SVD achieve a higher sum throughput than conventional MMSE precoding.

Antenna selection is an important issue for a distributed antenna-based small-cell network (DAN). This paper proposes a distributed antenna (DA) selection for DAN downlink using orthogonal frequency division multiplexing (OFDM) and space-time block coded (STBC) diversity. The proposed DA selection is an iterative algorithm which determines DA groups (each group consists of DAs communicating with a different user equipment (UE)) to maximize the downlink sum capacity by taking into account co-channel interference (CCI). In each iteration, one DA is added/removed to/from one of current DA groups if this increases the sum capacity by the largest amount. This is repeated until the sum capacity starts to decrease or by the prescribed number of times. It is shown by computer simulation that the proposed DA selection algorithm increases the 10% outage sum capacity by about 20% compared to the received signal power-based DA selection (no CCI is considered).

This paper considers the application of multiple-input multiple-output (MIMO) techniques to nonorthogonal multiple access (NOMA) systems. A new design of precoding and detection matrices for MIMO-NOMA is proposed and its performance is analyzed for the case with a fixed set of power allocation coefficients. To further improve the performance gap between MIMO-NOMA and conventional orthogonal multiple access schemes, user pairing is applied to NOMA and its impact on the system performance is characterized. More sophisticated choices of power allocation coefficients are also proposed to meet various quality-of-service requirements. Finally, computer simulation results are provided to facilitate the performance evaluation of MIMO-NOMA and also demonstrate the accuracy of the developed analytical results.

Abstract Single‐carrier transmission with frequency‐domain equalization (SC‐FDE) is widely known as a promising transmission technique providing low error probability with low peak‐to‐average power ratio (PAPR) of transmit signal. However, the low‐PAPR property of SC‐FDE cannot be maintained if multi‐level data modulation is introduced. The low‐PAPR property of SC‐FDE can be maintained by applying transmit filtering with roll‐off factor at the expense of spectrum efficiency. In this paper, we propose two types of selected mapping (SLM) to reduce the PAPR of SC‐FDE transmit signal. The first SLM technique is conducted in the frequency domain, where the phase rotation is applied to subcarriers similar to the SLM technique for orthogonal frequency division multiplexing transmission. The second SLM technique is conducted in the time domain, where the phase rotation is applied directly to data‐modulated symbol sequence. Computer simulation confirms that both SLM techniques are able to reduce the PAPR of SC‐FDE signal without significant degradation of bit‐error rate performance and spectrum efficiency. Copyright © 2016 John Wiley & Sons, Ltd.

Two important challenges facing 5G are energy efficiency and mobile users' mobility in heterogeneous wireless networks (HetNets). One of the important techniques for improving energy efficiency is base station (BS)'s switching between ON and OFF modes which allows the BS to turn off some its components in lower load situations. In this paper, we address user's seamless mobility problem and propose a handoff (HO) algorithm based on BS's estimated load. The proposed HO algorithm based on estimated load (PHA-EL) balances load by imposing HOs from highly loaded BSs to lightly loaded BSs. When a BS is overloaded, the user's quality of service (QoS) will degrade and therefore the PHA-EL is used to improve system throughput. The PHA-EL algorithm is combined with BSs which are able to switch between ON and OFF modes (PHA-EL/ON-OFF switching) in order to improve the energy efficiency of the system.Therefore, this algorithm achieves both energy- and spectral- efficiency. Simulation results indicate that the proposed algorithm yields better performance in terms of average number of HOs, average load per BS and average payoff per BS, compared to baseline algorithm.

In this paper, a non-orthogonal multiple access (NOMA) downlink scenario is considered, in which all nodes are equipped with multiple antennas. A new design of precoding and detection matrices for multiple-input-multiple-output (MIMO) downlink transmissions is proposed and its performance is analyzed by using the criteria of outage probabilities and diversity orders. To further enlarge the performance gap between MIMO-NOMA and conventional orthogonal multiple access schemes, user pairing is applied to NOMA and its impact on the system performance is characterized. Finally computer simulation results are provided to facilitate the performance evaluation of MIMO-NOMA and also demonstrate the accuracy of the developed analytical results.

In this paper, by exploiting the special features of temporal correlations of dynamic sparse channels that path delays change slowly over time but path gains evolve faster, we propose the structured matching pursuit (SMP) algorithm to realize the reconstruction of dynamic sparse channels. Specifically, the SMP algorithm divides the path delays of dynamic sparse channels into two different parts to be considered separately, i.e., the common channel taps and the dynamic channel taps. Based on this separation, the proposed SMP algorithm simultaneously detects the common channel taps of dynamic sparse channels in all time slots at first, and then tracks the dynamic channel taps in each single time slot individually. Theoretical analysis of the proposed SMP algorithm provides a guarantee that the common channel taps can be successfully detected with a high probability, and the reconstruction distortion of dynamic sparse channels is linearly upper bounded by the noise power. Simulation results demonstrate that the proposed SMP algorithm has excellent reconstruction performance with competitive computational complexity compared with conventional reconstruction algorithms.

Massive MIMO will be one of the technologies adopted in 5G cellular networks due to its ability to enhance transmission performance. However, resource management issues remain unsolved, especially with quality of service (QoS) requirements from users. This paper focuses on cell association and antenna allocation problems in such networks. We analyze the competitive situations where users in different classes with different QoS (i.e., data rate) requirement can choose to associate with any cell rationally and independently. Likewise, access points can allocate their antennas to different users. The users and access points are self-interested to maximize their own benefits in terms of data rate and total revenue, respectively. We formulate a hierarchical evolutionary game framework which is composed of the games for cell association and antenna allocation. We apply both deterministic and stochastic approaches to obtain the equilibrium solutions of the game.

In this paper, a cognitive machine-to-machine (M2M) communication network is considered, in which a cellular network shares the spectrum with the M2M communication network with M machine-type devices (MTDs), one half-duplex relay, and one MTD gateway for data gathering. One key challenge is that in the future 5G wireless networks, there will be billions of those small MTDs, and therefore, a MTD selection protocol is required for managing data transmission between MTDs. A joint buffer-aided MTD selection and power allocation protocol is proposed to maximize the MTDs' sum-rate provided that the induced interference to the cellular network is limited. In particular, in the proposed scheme, at each time slot and each subcarrier, the cognitive M2M network optimally decides on whether to be silent or to select either the relay or one of the MTDs for data transmission. To this end, for each MTD, there exists a buffer at the relay to avoid data loss. The closed-form expressions for the power coefficients of MTDs are calculated. Simulation results show that the proposed policy improves the sum-rate of the MTDs in comparison with the other proposed schemes for M2M communication without buffer.

In this paper, a novel spectrum efficient single-sideband single-carrier (SC) with frequency-domain equalization (SSB-FDE) using amplitude shift keying (ASK) modulation (ASK SSB-FDE) is proposed. Similar to the conventional SC transmission with FDE (SC-FDE), the ASK modulated symbol block to be transmitted is transformed by discrete Fourier transform (DFT) into frequency-domain signal. Then, inverse DFT (IDFT) is applied to the upper (or lower) sideband spectrum to obtain the time-domain SSB signal block. The cyclic prefix (CP) inserted SSB signal block is transmitted over a frequency-selective fading channel. At a receiver, the minimum mean square error (MMSE) based FDE is applied. ASK SSB-FDE has lower peak-to-average power ratio (PAPR) and better throughput performance than QAM SC-FDE when the throughput is plotted as a function of peak transmit SNR. This is confirmed by computer simulation assuming a frequency-selective Rayleigh fading channel.

Recently, Green Radio, which aims to reduce energy consumption of information and communication technologies (ICTs), has been concerned by telecommunication operators and researchers and can be applied to emergency scenarios. However, the communication system in emergency situation is pursuing not only energy reduction, but the large number of serviced users. In this paper, in order to provide telecommunication services for a great number of clients with low energy consumption in emergency scenarios, a capacity-and-energy efficient radio resource allocation mechanism is proposed, which is modeled as a Sigmoid-based optimization problem. Our simulation results demonstrate that compared with the conventional resource allocation algorithms, the proposed one achieves the largest capacity-and-energy efficiency, i.e., the largest number of serviced users per power unit.

Recently, we proposed a pseudo block coded single-carrier (PBC-SC) transmission using minimum mean square error (MMSE) based frequency-domain equalization and decoding (FDED) and show that MMSE based FDED achieves BER performance superior to 2-step decoding (which performs frequency-domain equalization and hard decision decoding separately). However, there still exists a large BER performance gap between MMSE based FDED and MF bound due to the presence of residual inter-symbol interference (ISI) after MMSE based FDED. In this paper, in order to narrow the performance gap, we propose frequency-domain block signal detection (FDBD) aided FDEDs for PBC-SC transmission: frequency-domain iterative interference cancellation (FDIC), maximum likelihood block sig-nal detection employing QR decomposition and M algorithm (QRM-MLBD) and belief propagation (BP). We compare, by computer simulation, the BER performances and the computa-tional complexities of three FDBD aided FDED schemes. It is shown that QRM-MLBD and BP can achieve almost the same BER performance as MF bound with much lower computational complexity than MMSE based FDED.

In a high mobility environment, single-carrier (SC) space-frequency block coding (SFBC) diversity achieves better bit error rate (BER) performance than SC space-time block coding (STBC) diversity. However, in a strong frequency-selective fading channel, the BER performance degrades due to the orthogonality distortion of SFBC codeword. In this paper, we propose a fre-quency-domain equalization (called robust FDE) suitable for SC-SFBC diversity in a frequency-selective fading. The robust FDE weights are jointly optimized based on minimum mean square error (MMSE) criterion taking into account channel variation within a SFBC codeword caused by frequency-selective fading. It is shown by computer simulation that proposed robust FDE al-ways achieves BER performance superior to conventional FDE whose weights are determined without considering the channel frequency variation within a SFBC codeword.

Analog single-carrier transmission with frequency-domain equalization (called analog SC-FDE) was recently proposed in order to improve performance of analog signal transmission. Analog SC-FDE signal spectrum has a complex conjugate relation between lower sideband (LSB) and upper sideband (USB) since analog signal is real-valued. Exploiting this property, the received LSB and USB subcarriers can be combined to obtain an additional frequency diversity gain. In this paper, a subcarrier combining method is proposed to improve the performance of analog SC-FDE. A theoretical analysis of normalized mean square error (NMSE) performance is presented to evaluate the effect of subcarrier combining and is confirmed by computer simulation. It is shown that subcarrier combining improves effectively the NMSE performance in multipath fading channel.

The demand for wireless resources is increasing at high pace. Heterogeneous networks (HetNets), i.e., network composed by base stations (BSs) with different coverage areas, are useful solutions to cope with this increasing demand. In this paper, we propose two handover (HO) algorithms.First HO algorithm is based on user equipment's (UE's) velocity, UE's position, UE's received signal strength (RSS) from BS and traffic load of BS.In the first phase of the first HO algorithm, UE employs parameters such as the distance of UE from its connected BS, velocity of UE and UE's RSS from its connected BS to determine the necessity of HO. If HO is needed, in the second phase, i.e., HO execution phase, UE selects the new BS based on the distance of UE from BS to which UE approaches, RSS and average traffic load of BS which is advertised through beacon signal. UE uses strength of received beacon signal as RSS. UE transmits the connection request signal to selected BS. Average traffic load means time average of traffic load. UE gets information of its position and its velocity via GPS. Second HO algorithm is based on only UE's RSS from BS and traffic load of BS. This HO algorithm has similar structure as the first one. However, in the first phase, only UE's instantaneous RSS and average RSS which means time average of RSS are employed to determine the necessity of HO by UE. In HOEP, UE selects the new BS based on instantaneous RSS, average RSS and average traffic load of BS. UE transmits the connection request signal to selected BS. A game-theoretic sleep mode algorithm is executed parallel to each HO algorithm in BS. The performance of the two proposed algorithms, such as total number of HOs, UE's throughput and system power consumption is evaluated by means of computer simulation.

This paper is concerned with cyclic prefix (CP) inserted broadband single-carrier (SC) multi-user multi-input multi-output (SC-MU-MIMO). The use of Tomlinson-Harashima precoding (THP) is effective to remove the inter-user interference (IUI). To remove the inter-symbol interference (ISI) caused by the channel frequency-selectivity, transmit equalization (TE) can be introduced. In the Degen and Rrühl's SC-MU-MIMO scheme (called as FD-SC-TETHP in this paper), THP and TE are performed separately in the frequency-domain. The modulo operation in THP suppresses the power increase caused by the IUI removal. TE can remove the ISI and the amplitude variation in the signals of a block received at each user, though it increases the signal power after equalization. This degrades significantly the received signal-to-noise power ratio (SNR). In this paper, we propose a time-domain SC-TETHP (TD-SC-TETHP), in which the ISI subtraction is performed together with IUI subtraction both in the time-domain. The modulo operation suppresses the power increase caused by both IUI and ISI removal. To prevent the amplitude variation, pre-removal of the received signal amplitude variation is inserted between the modulo operation and the precoding matrix multiplication. Uncoded average bit error rate (BER) performance achievable by our proposed TD-SC-TETHP is evaluated by computer simulation to confirm its superiority to the FD-SC-TETHP. Computational complexity is also discussed.

Large‐scale multiple‐input multiple‐output (MIMO) system is considered one of promising technologies to realise next‐generation wireless communication system (5G). So far, channel estimation problem is a big obstacle to develop large‐scale MIMO system design due to high computational complexity and curse of dimensionality, which are caused by the long delay spread as well as a large number of antennas. Hence, devising any low‐complexity channel estimation method could promote the successful development of the large‐scale MIMO system. Due to the fact that, large‐scale MIMO channels often exhibit sparse or/and cluster‐sparse structure, in this study, the authors propose an effective low‐complexity large‐scale MIMO channel estimation method by using affine combination of sparse adaptive filtering filters. First, problem formulation and standard affine combination of adaptive least mean square (LMS) filters are introduced. Then they propose an effective affine combination method with two sparse LMS filters and design an approximate optimum affine combiner according to stochastic gradient search method. Later, to verify the proposed algorithm for large‐scale MIMO channel estimation, both theoretical analysis and numerical simulations are provided to confirm effectiveness of the proposed algorithm which can achieve better estimation performance than the traditional methods.

In this paper, a green wireless communication system in which base stations are powered by renewable energy sources is considered. This system consists of a capacity-constrained renewable power supplier (RPS) and a base station (BS) that faces a predictable random connection demand from mobile user equipments (UEs). In this model, the BS, which is powered via a combination of a renewable power source and the conventional electric grid, seeks to specify the renewable power inventory policy, i.e., the power storage level. On the other hand, the RPS must strategically choose the energy amount that is supplied to the BS. An M/M/1 make-to-stock queuing model is proposed to investigate the decentralized decisions when the two parties optimize their individual costs in a noncooperative manner. The problem is formulated as a noncooperative game whose Nash equilibrium (NE) strategies are characterized to identify the causes of inefficiency in the decentralized operation. A set of simple linear contracts are introduced to coordinate the system so as to achieve an optimal system performance. The proposed approach is then extended to a setting with one monopolistic RPS and N BSs that are privately informed of their optimal energy inventory levels. In this scenario, we show that the widely used proportional allocation mechanism is no longer socially optimal. To make the BSs truthfully report their energy demand, an incentive compatible (IC) mechanism is proposed for our model. Simulation results show that using the green energy can present significant traditional energy savings for the BS when the connection demand is not heavy. Moreover, the proposed scheme provides valuable energy cost savings by allowing the BSs to smartly use a combination of renewable and traditional energy, even when the BS has a heavy traffic of connections. Also, the results show that performance of the proposed IC mechanism will be close to the social optimal when the green energy production capacity increases.

Abstract Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advantages of both least mean square (LMS) and least mean fourth (LMF). The advantage of LMS is fast convergence speed while its shortcoming is suboptimal solution in low signal‐to‐noise ratio (SNR) environment. On the contrary, the advantage of LMF algorithm is robust in low SNR while its drawback is slow convergence speed in high SNR case. Many finite impulse response systems are modeled as sparse rather than traditionally dense. To take advantage of system sparsity, different sparse LMS algorithms withlp‐LMS andl0‐LMS have been proposed to improve adaptive identification performance. However, sparse LMS algorithms have the same drawback as standard LMS. Different from LMS filter, standard LMS/F filter can achieve better performance. Hence, the aim of this paper is to introduce sparse penalties to the LMS/F algorithm so that it can further improve identification performance. We propose two sparse LMS/F algorithms using two sparse constraints to improve adaptive identification performance. Two experiments are performed to show the effectiveness of the proposed algorithms by computer simulation. In the first experiment, the number of nonzero coefficients is changing, and the proposed algorithms can achieve better mean square deviation performance than sparse LMS algorithms. In the second experiment, the number of nonzero coefficient is fixed, and mean square deviation performance of sparse LMS/F algorithms is still better than that of sparse LMS algorithms. Copyright © 2013 John Wiley & Sons, Ltd.

To realize high-speed communication, broadband transmission has become an indispensable technique in the next-generation wireless communication systems. Broadband channel is often characterized by the sparse multipath channel model, and significant taps are widely separated in time, and thereby, a large delay spread exists. Accurate channel state information is required for coherent detection. Traditionally, accurate channel estimation can be achieved by sampling the received signal with large delay spread by analog-to-digital converter ADC at Nyquist rate and then estimate all of channel taps. However, as the transmission bandwidth increases, the demands of the Nyquist sampling rate already exceed the capabilities of current ADC. In addition, the high-speed ADC is very expensive for ordinary wireless communication. In this paper, we present a novel receiver, which utilizes a sub-Nyquist ADC that samples at much lower rate than the Nyquist one. On the basis of the sampling scheme, we propose a compressive channel estimation method using Dantzig selector algorithm. By comparing with the traditional least square channel estimation, our proposed method not only achieves robust channel estimation but also reduces the cost because low-speed ADC is much cheaper than high-speed one. Computer simulations confirm the effectiveness of our proposed method. Copyright © 2013 John Wiley & Sons, Ltd.

Abstract This paper studies normalized least mean square‐based adaptive sparse filtering algorithms for estimating multiple‐input multiple‐output (MIMO) channels. Although the MIMO channel is often modeled as sparse, traditional normalized least mean square‐based filtering algorithm never takes the advantage of the inherent sparse structure information and thus causes some performance loss. Unlike the traditional method, the proposed two adaptive sparse channel estimation methods exploit the sparse structure information of MIMO channels. To validate the effectiveness of proposed MIMO channel estimates, theoretical analysis and simulation results are provided. We derive steady‐state mean‐square deviations of the proposed MIMO channel estimates and theoretically show that it is better than the traditional one. Moreover, their performance advantages are confirmed by computer simulations. Copyright © 2014 John Wiley & Sons, Ltd.

Multihop cooperative communication is emerging as a key concept to extend the coverage area of the network and potentially increase the capacity. The spectral efficiency of such networks can be improved by adapting the transmission to time-varying channel conditions, referred to as incremental relaying. Although such incremental relaying concepts are progressively being studied, many challenges, such as erroneous transmissions by intermediate nodes and end-to-end delay of the network, limit its practical use due to lack of an efficient implementation. This paper proposes an efficient multihop incremental relaying technique. In this method, erroneous relay forwarding is mitigated, and the overhead for coordination among nodes is reduced by exploiting the implicit feedback channel available due to the broadcast nature of wireless transmissions. The proposed scheme fully leverages the benefit of overhearing and eliminates the additional feedback slots required for validation. Further, it ensures reliable forwarding of information, which optimizes the throughput of multihop networks. Thorough analysis of the proposed scheme is performed under different deployment environments, and the theoretical analyses presented in this paper are supported with results from extensive simulation studies.

Compared with standard cyclic prefix OFDM (CP-OFDM), time domain synchronous OFDM (TDS-OFDM) can achieve a higher spectrum efficiency by using the known training sequence instead of CP as the guard interval. However, TDS-OFDM suffers from reduced energy efficiency and performance loss due to the existing mutual inferences. In this paper, based on the newly emerging theory of structured compressive sensing (SCS), we propose a reliable and energy-efficient TDS-OFDM transmission scheme with reduced guard interval power (which is impossible for CP-OFDM) by designing a channel estimation scheme with high accuracy. The wireless channel properties including channel sparsity and inter-channel correlation, which are usually not considered in conventional OFDM schemes, have been exploited. We further exploit the worst-case system design principle to extract multiple interference-free regions of small size to simultaneously reconstruct multiple channels of large size without iterative interference cancellation. In this way, the guard interval power in TDS-OFDM can be reduced to achieve a 20% higher energy efficiency than standard CP-OFDM, and the system reliability can be also improved in fast fading channels.

Accurate channel estimation is essential for broadband wireless communications. Adaptive sparse channel estimation schemes based on normalized least mean square (NLMS) have been proposed to exploit channel sparsity for improved performance. However, their performance bound as derived in this paper indicates that the invariable step size (ISS) usually used for iteration in these schemes would lead to performance loss or/and slow convergence speed as well as high computational cost. To solve this problem, based on the observation that a large step size is preferred for fast convergence while a small step size is preferred for accurate estimation, we then propose to replace the ISS by the variable step size (VSS) to improve the performance of sparse channel estimation. The key idea is that the VSS can be adaptive to the estimation error in each iteration, i.e., a large step size is used in the case of large estimation error to accelerate the convergence speed, while a small step size is used when the estimation error is small to improve the steady-state estimation accuracy. Finally, simulation results verify that better mean square error (MSE) and bit error rate (BER) performance could be achieved by the proposed scheme.

In this paper, we address the resource allocation (RA) problem for uplink single input multiple output (SIMO) single carrier frequency division multiple access (SC-FDMA). A novel RA algorithm for joint user scheduling and resource block allocation is presented. Particularly, with the aim of improving the spectral efficiency (SE) and reducing the computational complexity, a sub-optimal power projection method based on users' spatial correlation is employed, which chooses the users for each RB. A parametric multiple access channel (MAC) model is used for modelling the receive antenna correlation at the base station. Our simulation results show that the proposed scheme improves the the SE considerably, while keeping the complexity at an acceptable level. We also investigate the variation of different system design parameters, i.e., RB size, number of receive antenna, etc, on the SIMO SC-FDMA uplink SE, to shed insight on the role of these parameters in system SE optimization.

Single-carrier (SC) space-time block coded (STBC) time-division duplex (TDD) transmission achieves a good bit-error rate (BER) performance while the channel state information (CSI) is not required at the mobile terminal (MT). However, in a high mobility environment, the channel changes within a STBC codeword and the BER performance significantly degrades due to the interference caused by the orthogonality distortion of STBC codeword. In this paper, we propose a multi-block (MB)-frequency-domain equalization (FDE) for SC-STBC-TDD transmission in a high mobility environment. The STBC codeword consists of multiple signal blocks. The proposed MB-FDE uses jointly optimized multiple FDE weight matrices, each associated with each signal block in a STBC codeword. We evaluate, by computer simulation, the BER performance when using the proposed transmit/receive MB-FDE and show that the proposed MB-FDE achieves a good BER performance in a high mobility environment.

Recently, we proposed interference-aware channel segregation based dynamic channel assignment (IACS-DCA) which forms a channel reuse pattern with low co-channel interference (CCI) in a distributed manner. The transmission performance of a wireless station (STA) located far from access points (APs) degrades due to path loss and shadowing loss. AP cooperative diversity is a well-known technique to improve the transmission performance. Since IACS-DCA operates so as to assign different channels to different APs located nearby each other, it is not an easy task to introduce AP cooperative diversity to a wireless network using IACS-DCA. In this paper, we propose an AP grouping and channel selection method for AP cooperative diversity in a wireless network using IACS-DCA. By computer simulation, we show that the proposed AP cooperative diversity can improve the transmission performance.

Sparse system identification problems often exist in many applications, such as echo interference cancellation, sparse channel estimation, and adaptive beamforming. One of popular adaptive sparse system identification (ASSI) methods is adopting only one sparse least mean square (LMS) filter. However, the adoption of only one sparse LMS filter cannot simultaneously achieve fast convergence speed and small steady-state mean state deviation (MSD). Unlike the conventional method, we propose an improved ASSI method using affine combination of two sparse LMS filters to simultaneously achieving fast convergence and low steady-state MSD. First, problem formulation and standard affine combination of LMS filters are introduced. Then an approximate optimum affine combiner is adopted for the proposed filter according to stochastic gradient search method. Later, to verify the proposed filter for ASSI, computer simulations are provided to confirm effectiveness of the proposed filter which can achieve better estimation performance than the conventional one and standard affine combination of LMS filters.

DS-CDMA allows all accessing users to share the same carrier frequency and hence, can alleviate the sophisticated channel management problem. Recently, we investigated a distributed antenna network (DAN) using direct-sequence code division multiple access (DS-CDMA) with joint antenna diversity and equalization and showed that DAN achieves higher uplink capacity than centralized antenna network (CAN). The uplink capacity is limited due to multiple access interference (MAI). In this paper, to further improve the uplink capacity, we propose a complexity-reduced per-antenna MAI cancellation before diversity combining, which is suitable for DAN using DS-CDMA. In the per-antenna MAI cancellation, first, interfering users on each antenna are sorted in descending order of the instantaneous received power. Then, a predetermined number of interfering users having the highest received powers are selected on each antenna to be cancelled in the frequency-domain before diversity combining. It is shown by computer simulation that per-antenna MAI cancellation before diversity combining achieves almost the same uplink capacity as full MAI cancellation after diversity combining.

In this paper, we propose a fairness-controlled multiuser scheduling and resource allocation (RA) algorithm for uplink spatial division multiple access (SDMA)/ single carrier frequency division multiple access (SC-FDMA). In fact, with the aim of improving the spectral efficiency (SE) and at the same time controlling the network fairness, a sub-optimal power projection method based on users' spatial correlation is employed, which chooses the users for each resource block (RB). We assume a single-input multiple-output (SIMO) scheme with correlation at receive antenna. By changing the maximum allowed number of simultaneously accessing users, we can choose the desired balance between SE and the fairness. Numerical analysis verifies that the proposed scheme improves the SE considerably at the target defined fairness level. We also investigate the variations in fairness for different system design parameters, i.e., RB size, number of receive antenna, etc.

In this paper, we propose a pseudo block-coded SC transmission with frequency-domain equalization (FDE). We call this scheme as pseudo block-coded SC with FDE (PBCSC-FDE). A concatenation of block encoding matrix, interleaving matrix, DFT matrix, mapping matrix and channel matrix can be viewed as an equivalent MIMO channel and FDE and block decoding can be jointly performed based on the minimum mean square error (MMSE) criterion. We evaluate, by computer simulation, the average bit error rate (BER) performance of PBCSC-FDE and show that its achievable BER performance is superior to a 2-step decoding which performs FDE and hard decision block decoding separately.

Single-carrier (SC) transmission using frequency-domain space-time block coded joint transmit/receive diversity (FD-STBC-JTRD) combined with transmit frequency-domain equalization (FDE) obtains full spatial diversity gain and frequency diversity gain. Recently, we derived the optimal transmit frequency-domain equalization (FDE) for SC FD-STBC-JTRD and showed that the optimal transmit FDE, which uses multiple weight matrices corresponding to multiple coded blocks in a STBC code-word, achieves the received signal-to-interference plus noise power ratio (SINR) 1/RSTBC times higher than the conventional transmit FDE which uses the single weight matrix over a STBC code-word, where RSTBC denotes the STBC code rate. However, our past study of SC FD-STBC-JTRD with the optimal transmit FDE assumed ideal channel estimation. In this paper, we provide theoretical analysis of the received SINR and the conditional bit error rate (BER) of SC FD-STBC JTRD with cyclic delay pilot channel estimation (CDP-CE) and discuss the impact of channel estimation error. Then, we evaluate, by computer simulation, the average BER performance when using SC FD-STBC-JTRD with the optimal transmit FDE and show that the optimal transmit FDE can achieve the received SINR 1/RSTBC times higher than the conventional transmit FDE even in the presence of the channel estimation error.

Recently, we have studied frequency-domain space-time block coded joint transmit/receive diversity (FD-STBC-JTRD) for distributed antenna network (DAN). The channel of DAN can be modeled as doubly-selective (time- and frequency-selective) Nakagami-Rice fading channel. FD-STBC-JTRD requires accurate channel state information (CSI). However, in a high mobility environment, channel estimation is a problem. In this paper, we introduce sparse channel estimation scheme and evaluate, by computer simulation, the downlink throughput performance of DAN using FD-STBC-JTRD in a high mobility environment. It is shown that the sparse channel estimation works well even in a high mobility environment.

Recently, we proposed a novel analog signal transmission technique called analog single-carrier transmission with frequency-domain equalization (analog SC-FDE) and showed that analog SC-FDE achieves better normalized mean square error (NMSE) performance than conventional analog signal transmission. In order to achieve further performance improvement, transmit/receive antenna diversity technique is effective. In digital wireless communications, joint space-time transmit diversity (STTD) and receive antenna diversity is well known as a promising antenna diversity technique which achieves a high diversity order (equal to the product of the number of transmit antennas and the number of receive antennas) with a simple signal processing. In this paper, analog SC- FDE using joint STTD and receive antenna diversity is proposed. A theoretical analysis of the NMSE performance is derived to evaluate the transmission performance of the proposed scheme and is confirmed by computer simulation. We show that joint STTD and receive antenna diversity can significantly improve the NMSE performance of our proposed analog SC-FDE.

Channel estimation problem is one of the key technical issues for broadband multiple‐input–multiple‐output (MIMO) signal transmission. To estimate the MIMO channel, a standard least mean square (LMS) algorithm was often applied to adaptive channel estimation because of its low complexity and stability. The sparsity of the broadband MIMO channel can be exploited to further improve the estimation performance. This observation motivates us to consider adaptive sparse channel estimation (ASCE) methods using sparse LMS (ASCE‐LMS) algorithms. However, conventional ASCE methods have two main drawbacks: (i) sensitivity to random scaling of training signal and (ii) poor estimation performance in low signal‐to‐noise ratio (SNR) regime. The former drawback is tackled by proposing novel ASCE‐NLMS algorithms. ASCE‐NLMS mitigates interference of random scale of training signal and therefore it improves its algorithm stability. It is well‐known that stable sparse normalised least‐mean fourth (NLMF) algorithms can achieve better estimation performance than sparse NLMS algorithms. Therefore the authors propose an improved ASCE method using sparse NLMF algorithms (ASCE‐NLMF) to improve the estimation performance in low SNR regime. Simulation results show that the proposed ASCE methods are shown to achieve better performance than conventional methods, that is, ASCE‐LMS by computer simulations. Also, the stability of the proposed methods is confirmed by theoretical analysis.

The current and future communication and sensing systems such as cognitive radio, radar, or sensor network include a network of multiple communication modules/devices or sensors. The network of communication modules/devices or sensors should operate with multiple goals managed by an intelligent platform network that can manage the dynamics of each device/sensor to meet the common goals of the platform, rather than each device/sensor to operate as an independent system. Therefore, it is significant to perform cooperative communication and sensing within and between platforms of sensors and their communication modules/devices. This special issue contains 14 papers selected from submissions to the 6th International Conference on Communications and Networking in China (CHINACOM 2011), with further extension and satisfactory external peer reviews. These papers highlight some of the current research interests and achievements in the area of cooperative communications and sensing. The topics include cognitive radio, spectrum sensing, MIMO system, radar, compressive sensing, and localization. The paper by Huang et al. analyzed the performance bonds of a wireless relay system that consists of several relays stations working on both amplifier-and-forward (AF) and decode-and-forward (DF) algorithms. The outage probability behavior of the proposed mixed AF and DF relay systems under independent Nakagami-m fading channels was studied. The trade-off between the complexity and performance issues was also discussed. The paper by Sun et al. presented a review on evolution from symbol-level space-time coded MIMO to chip-level space-time coded MIMO. It discussed the characteristics and limitations of traditional symbol-level space-time coding schemes. The proposed chip-level space-time coded MIMO works well even in a fast fading channel in addition to its flexibility to achieve diversity and multiplexing gains simultaneously in varying channel environments. The paper by Liu et al. studied cognitive radio and proposed a double cooperative detection scheme based on weighed combination in order to improve the global detected performance of the cooperative detection. The paper by Peng and Adachi analyzed the performance of a single-carrier frequency domain adaptive antenna array (SC-FDAAA) in a distributed antenna network (DAN) system. In order to make it clear whether the performance of SC-FDAAA can benefit from the distributed nature of DAN system or not, they made a comparison between DAN system and the traditional cellular system, that is, central antenna network system. The paper by Li et al. proposed a conception on the terahertz communication system for plasma sheath penetration. An idea based on the capability of radiation from the terahertz communication system to penetrate the plasma sheath was proposed to provide the theoretical basis for real-time communication with the nearcraft. The paper by Zhang et al. studied single-carrier frequency-domain equalization (SC-FDE). The feasibility of building SC-FDE system was explored by comparing performance with orthogonal frequency division multiplexing (OFDM). It studied on a dual-mode (DD-LMS+MCMA) blind equalization algorithm applied in a single-carrier system. The simulation model of image transmission in SC-FDE system was built with better result through the comparative analysis of image. The paper by Wu et al. proposed a new compressive sensing-based compression and recovery ultra-wideband (UWB) communication system. Real-world UWB signal was collected and processed to evaluate the performance of our proposed system. Simulation results showed that the data could be perfectly recovered if the compression ratio does not exceed 2.5:1 when Bernoulli matrix is chosen as the sensing matrix. The paper by Zou et al. focused on improving the system capacity of 60GHz wireless personal area networks and put forward an effective timeslot allocation scheme for spatial reuse, which combines the existing exclusive-region-based scheduling algorithm with simple power control. The paper by Huang and Pi proposed a GPS-based positioning and navigation with aid of wireless network positioning scheme, which utilizes the existing resources of the wireless communication network to provide the cheaper and more accurate urban positioning service with the higher survivability. The paper by Arianpoo et al. presented a survey on applications of network coding to improve TCP performance over wireless mesh networks (WMNs). It provided a thorough survey of TCP performance issues over WMNs and the available solutions to address these issues. Among the existing methods, network coding and the ways that TCP interacts with network-coded systems were focused. Some open research areas in this field were suggested. The paper by Yu et al. proposed a combined code reuse scheme with two-dimensional orthogonal variable spreading factor codes assignment algorithm for uplink multi-user/multi-rate block spread multi-cellular code division multiple access (CDMA). It was confirmed by the computer simulation that the proposed code assignment algorithm improves the code reuse efficiency while achieving lower blocking probability than traditional CDMA. The paper by Yang et al. proposed a relatively complete and robust optimization model under the scenario where multi-secondary users cooperatively sense multi-channels. The objective of this model was to maximize the system throughput, while aiming to jointly optimize the parameters including the sensing time and the weight coefficients of the sampling results. The results showed the performance advantage of the proposed model on improving the system throughput by comparing with other state-of-the-art optimization models. The paper by Shi et al. proposed a new linear fractional shift invariant system structure associated with the fractional Fourier transform, and the linear time-invariant systems were noted as special cases. The eigenfunctions and eigenvalues of the new LFSI systems were presented. The paper by Wu et al. studied channel estimation algorithms for cooperative spectrum sensing in AF cooperative system. The influence of channel estimation error to system performance was firstly deduced, and then linear minimum mean-square error (LMMSE) channel estimation algorithm with delay time-domain windowing technique (LMMSE-DTW) and modified singular value decomposition based LMMSE algorithm (SVD-LMMSE) were proposed to improve the channel estimation performance for CDMA system and OFDM system, respectively. We would like to thank all authors for contributing papers to the special issue. We appreciate the staff of Wireless Communications and Mobile Computing for their support in editing this special issue. Qilian Liang is a Professor at the Department of Electrical Engineering, University of Texas at Arlington (UTA). He received the BS degree from Wuhan University in 1993, the MS degree from Beijing University of Posts and Telecommunications in 1996, and the PhD degree from University of Southern California (USC) in May 2000, all in Electrical Engineering. Prior to joining the faculty of the University of Texas at Arlington in August 2002, he was a Member of Technical Staff in Hughes Network Systems Inc. at San Diego, California. His research interests include wireless sensor networks, wireless communications, compressive sensing, smart grid, signal processing for communications, fuzzy logic systems and applications, and so on. Dr Liang has published more than 250 journal and conference papers and seven book chapters. He received the 2002 IEEE Transactions on Fuzzy Systems Outstanding Paper Award, the 2003 US Office of Naval Research (ONR) Young Investigator Award, the 2005 UTA College of Engineering Outstanding Young Faculty Award, the 2007, 2009, 2010 US Air Force Summer Faculty Fellowship Program Award, the 2012 UTA College of Engineering Excellence in Research Award, and the 2013 UTA Outstanding Research Achievement Award. Victor C. M. Leung received the BASc (Hons) degree in electrical engineering from the University of British Columbia (UBC) in 1977 and was awarded the APEBC Gold Medal as the head of the graduating class in the Faculty of Applied Science. He attended graduate school at UBC on a Natural Sciences and Engineering Research Council Postgraduate Scholarship and completed the PhD degree in electrical engineering in 1981. From 1981 to 1987, Dr Leung was a Senior Member of Technical Staff and satellite system specialist at MPR Teltech Ltd., Canada. In 1988, he was a Lecturer in the Department of Electronics at the Chinese University of Hong Kong. He returned to UBC as a faculty member in 1989 and currently holds the positions of Professor and TELUS Mobility Research Chair in Advanced Telecommunications Engineering in the Department of Electrical and Computer Engineering. Dr Leung has co-authored more than 700 technical papers in international journals and conference proceedings, 29 book chapters, and co-edited eight book titles. Several of his papers had been selected for best paper awards. His research interests are in the areas wireless networks and mobile systems. Dr Leung is a registered professional engineer in the Province of British Columbia, Canada. He is a Fellow of IEEE, the Royal Society of Canada, the Engineering Institute of Canada, and the Canadian Academy of Engineering. He was a Distinguished Lecturer of the IEEE Communications Society. He is a member of the editorial boards of the IEEE Wireless Communications Letters, Computer Communications, and several other journals and has previously served on the editorial boards of the IEEE Journal on Selected Areas in Communications—Wireless Communications Series, IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Computers, and Journal of Communications and Networks. He has guest-edited many journal special issues and contributed to the organizing committees and technical program committees of numerous conferences and workshops. He was a recipient of the IEEE Vancouver Section Centennial Award and 2012 UBC Killam Research Prize. Weixiao Meng received the BEng, MEng, and PhD degrees from Harbin Institute of Technology (HIT), Harbin, China, in 1990, 1995, and 2000, respectively. From 1998 to 1999, he worked at NTT DoCoMo on adaptive array antenna and dynamic resource allocation for beyond 3G as a senior visiting researcher. He is now a full professor at the School of Electronics and Information Engineering of HIT. His research interests include broadband wireless communications and networking, MIMO, GNSS receiver, and wireless localization technologies. He has published three books and over 190 papers on journals and international conferences. He is the Chair of IEEE Communications Society Harbin Chapter, a senior member of the IEEE ComSoc, IET, the China Institute of Electronics, and the China Institute of Communication. He has been an editorial board member for Wiley's WCMC Journal since 2010 and the area editor for PHYCOM journal since 2014. He acted as leading TPC co-chair of ChinaCom2011, leading Services and Applications track co-chair of IEEE WCNC2013, Awards co-chair of IEEE ICC2015, and Wireless Networking Symposia co-Chair. In 2005, he was honored provincial excellent returnee and selected into New Century Excellent Talents (NCET) plan by Ministry of Education, China, in 2008. Fumiyuki Adachi received the BS and DrEng degrees in electrical engineering from Tohoku University, Sendai, Japan, in 1973 and 1984, respectively. In April 1973, he joined the Electrical Communications Laboratories of Nippon Telegraph & Telephone Corporation (now NTT) and conducted various types of research related to digital cellular mobile communications. From July 1992 to December 1999, he was with NTT Mobile Communications Network, Inc. (now NTT DoCoMo, Inc.), where he led a research group on wideband/broadband CDMA wireless access for IMT-2000 and beyond. Since January 2000, he has been with Tohoku University, Sendai, Japan, where he is a distinguished Professor of Communications Engineering at the Graduate School of Engineering. His research interest is in the areas of wireless signal processing and networking including broadband wireless access, equalization, transmit/receive antenna diversity, MIMO, adaptive transmission, channel coding, and so on. From October 1984 to September 1985, he was a United Kingdom SERC Visiting Research Fellow in the Department of Electrical Engineering and Electronics at Liverpool University. Dr Adachi is an IEEE Fellow and a VTS Distinguished Lecturer for 2011 to 2013. He is a co-recipient of the IEEE Vehicular Technology Transactions Best Paper of the Year Award 1980 and again 1990 and also a recipient of Avant Garde award 2000. He is a Fellow of Institute of Electronics, Information and Communication Engineers of Japan (IEICE) and is a recipient of IEICE Achievement Award 2002 and a co-recipient of the IEICE Transactions Best Paper of the Year Award 1996, 1998, and again 2009. He is a recipient of Thomson Scientific Research Front Award 2004, Ericsson Telecommunications Award 2008, Telecom System Technology Award 2009, Prime Minister Invention Prize 2010, British Royal Academy of Engineering Distinguished Visiting Fellowship 2011, and KDDI Foundation Research Award 2012.

ABSTRACT Single‐carrier frequency domain adaptive antenna array (SC‐FDAAA) has been proposed and proved in our previous study to be effective in suppressing multiple access interference in a severely frequency selective fading channel. In this paper, we studied the performance of SC‐FDAAA in a distributed antenna network (DAN). To make it clear whether the performance of SC‐FDAAA can benefit from the distributed nature of DAN or not, we made a comparison between DAN and the traditional cellular network, that is, central antenna network. The bit error rate distribution and the system capacity (both link capacity and cellular link capacity) are presented. It is shown that by using the SC‐FDAAA, cellular link capacity is maximized by using single frequency reuse. In addition, the capacity of SC‐FDAAA can also benefit from the distributed nature of DAN. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT The two‐dimensional (2D) block spread code division multiple access (CDMA) can avoid the uplink multiple‐access interference with low‐complexity single‐user detection in a slow fading channel and, therefore, is very attractive. In the 2D spreading, orthogonal variable spreading factor (OVSF) is used for spreading; an important problem is how to efficiently assign the limited resource of OVSF codes to users with different data rates, while meeting the requirement of quality of service in a multi‐cell environment. In this paper, it is shown that the code reuse can improve the code reuse efficiency and the proposed code reuse scheme combined with code assignment algorithm can allow flexible multi‐rate uplink transmission. The computer simulation confirms that the proposed code assignment algorithm improves the code reuse efficiency while achieving lower blocking probability than traditional CDMA. Copyright © 2012 John Wiley & Sons, Ltd.

Least mean square (LMS)-type adaptive sparse algorithms have been attracting much attention on sparse multipath channel estimation (SMPC) due to their two advantages: low computational complexity and reliability. By introducing ℓ1-norm sparse constraint function into LMS algorithm, both zero-attracting least mean square (ZA-LMS) and reweighted zero-attracting least mean square (RZA-LMS) have been proposed for SMPC. It is well known that the performance of the SMPC is decided by regularization parameter which balances channel estimation error and sparse penalty strength. However, optimal regularization parameter selection has not yet considered in the two proposed algorithms. Based on the compressive sensing theory, in this paper, we explain the mathematical relationship between Lasso and LMS-type adaptive sparse algorithms. Later, an approximate optimal regulation parameter selection method is proposed for ZA-LMS and RZA-LMS, respectively. Monte Carlo based computer simulations are presented to show the effectiveness of our propose method.

Broadband data services are demanded even under high mobility environment, such as high-speed railway. In this paper, we consider single-carrier (SC) linearly distributed antenna network (DAN). The distributed antenna-mobile terminal (MT) link will be a line-of-sight link and therefore, fading can be characterized as the frequency-selective Nakagami-Rice fading. Distributed antenna diversity using single frequency network (SFN) can mitigate the impacts of path and shadowing losses as well as the frequency-selective fading. In this paper, frequency-domain space-time block coded-joint transmit/receive diversity (FD-STBC-JTRD) is employed as SFN linearly distributed antenna diversity. It is confirmed by computer simulation that FD-STBC-JTRD is a powerful diversity to improve the transmission performance under a high mobility environment.

In this paper, a new analog signal transmission technique called analog single-carrier transmission with frequency-domain equalization (analog SC-FDE) is proposed. The proposed analog SC-FDE applies discrete Fourier transform (DFT), frequency-domain spectrum shaping and mapping, inverse DFT (IDFT), and cyclic prefix insertion before transmission. At the receiver, one-tap frequency-domain equalization (FDE) is applied to take advantage of the channel frequency-selectivity. As an example, in this paper, the analog voice transmission is considered. By computer simulation, we evaluate the normalized mean square error (NMSE) performance to show that analog SC-FDE achieves better NMSE performance than conventional analog signal transmission scheme.

Global connectivity, at anyplace and anytime, to provide high-speed, high-quality, and reliable communication channels, is now becoming a reality. The credit mainly goes to the recent technological advances in wireless communications which consist of a wide range of technologies and applications to fulfill the particular needs of end-users in different deployment scenarios (Bluetooth, Wi-Fi, WiMAX, and 3G/4G cellular systems). In such a heterogeneous wireless environment, one of the key ingredients to provide efficient ubiquitous computing, is the design of intelligent handoff algorithms, which select the optimal target network. This paper presents a novel approach for the design and implementation of a multi-criteria vertical handoff decision algorithm for heterogeneous wireless networks to achieve seamless mobility while maximizing end-users' satisfaction. After weighting the network parameters, a ranking algorithm based on the fuzzy extension of the the Techniques for Order Preference by Similarity to Ideal Solution (TOPSIS) is used to prioritize all the available networks within the coverage of the mobile user. Simulation results are provided and compared with a benchmark for a single user scenario.

Accurate channel state information (CSI) is required for coherent detection in time-variant multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) modulation. One of low-complexity and stable adaptive channel estimation (ACE) approaches is the normalized least mean square (NLMS)-based ACE. However, it cannot exploit the inherent sparsity of MIMO channel which is characterized by a few dominant channel taps. In this paper, we propose two adaptive sparse channel estimation (ASCE) methods to take advantage of such sparse structure information for time-variant MIMO-OFDM systems. Unlike traditional NLMS-based method, two proposed methods are implemented by introducing sparse penalties to the cost function of NLMS algorithm. Computer simulations confirm obvious performance advantages of the proposed ASCEs over the traditional ACE.

Joint transmit/receive frequency-domain equalization based on minimum mean-square error criterion (joint Tx/Rx MMSE-FDE) is a promising frequency-domain-based technique suppressing inter-symbol interference (ISI) in broadband single-carrier (SC) transmission. However, it changes the frequency-domain spectrum shape and hence increases the peak-to-average power ratio (PAPR) of transmit signal. In this paper, we introduce the selective mapping (SLM), which is typically used in orthogonal frequency division multiplexing (OFDM), to reduce PAPR of SC transmission using joint Tx/Rx MMSE-FDE. The SLM is applied to the frequency-domain SC signal after applying the transmit FDE (Tx-FDE) and prior to inverse fast Fourier transform (IFFT). It is shown, by computer simulation, that the SLM can reduce PAPR without significant effect on bit-error rate (BER). Performance of SLM is also evaluated in various phase-rotation sequence types, in both deterministic and random points of views, and number of candidates. Computational complexity of the proposed transmission scheme employing SLM algorithm is also discussed.

Broadband signal transmission over frequency-selective fading channel often requires accurate channel state information at receiver. One of the most attracting adaptive channel estimation (ACE) methods is least mean square (LMS) algorithm. However, its performance is often degraded by random scaling of input training signal. To overcome this degradation, in this paper we consider the use of standard least mean square/fourth (LMS/F) algorithm. Since the broadband channel is often described by sparse channel model, such sparsity could be exploited as prior information. First, we propose an adaptive sparse channel estimation (ASCE) method with zero-attracting LMS/F (ZA-LMS/F) algorithm by introducing an ℓ1-norm sparse constraint into the cost function. Then, to exploit the sparsity more effectively, an improved ASCE with reweighted zero-attracting LMS/F (RZA-LMS/F) algorithm is proposed. For different channel sparsity, we propose a Monte Carlo method for a regularization parameter selection in RA-LMS/F and RZA-LMS/F to achieve better steady-state estimation performance. Simulation results show that the proposed ASCE methods achieve better estimation performance than the conventional one.

Multihop cooperative communication is emerging as a key concept to extend the coverage area and potentially increase the capacity of wireless networks. With multiple hops, processing at the forwarding nodes is a major source of error propagation. In this context, a novel spectrally efficient transmission scheme with error protection for such networks is proposed in this paper. The proposed scheme retains the spatial diversity and enhances the bandwidth efficiency by integrating incremental redundancy concepts into such cooperative multihop systems. The guard against error propagation and the overhead for coordination among multiple nodes in such networks is mitigated by the implicit feedback channel available due to broadcast nature of wireless transmissions. The proposed scheme fully leverages the benefit of overhearing and eliminates the additional feedback slots required for validation. Further, it ensures reliable forwarding of information which optimizes the throughput of multihop networks. Theoretical framework is also developed for the proposed system and supported with results from extensive simulation studies.

Channel estimation problem is one of the key technical issues in time-variant multiple-input multiple-output (MIMO) communication systems. To estimate the MIMO channel, least mean square (LMS) algorithm was applied to adaptive channel estimation (ACE). Since the MIMO channel is often described by sparse channel model#65292;such sparsity can be exploited to improve the estimation performance by adaptive sparse channel estimation (ASCE) methods using sparse LMS algorithms. However, conventional ASCE methods have two main drawbacks: 1) sensitive to random scale of training signal and 2) unstable in low signal-to-noise ratio (SNR) regime. To overcome the two harmful factors, in this paper, we propose a novel ASCE method using normalized LMS (NLMS) algorithm (ASCE-NLMS). In addition, we also proposed an improved ASCE method using normalized least mean fourth (NLMF) algorithm (ASCE-NLMF). Two proposed methods can exploit the channel sparsity effectively. Also, stability of the proposed methods is confirmed by mathematical derivation. Computer simulation results show that the proposed sparse channel estimation methods can achieve better estimation performance than conventional methods.

Channel state information (CSI) is required at receiver in orthogonal frequency division modulation (OFDM) communication systems due to the fact that frequency-selective fading channel leads to inter- symbol interference (ISI) over data transmission. Broadband channel model is often described by very few dominant channel taps and they can be probed by sparse channel estimation (SCE) methods, e.g., subspace pursuit (SP) algorithm, can take the advantage of sparse structure effectively in broadband channels as for prior information. However, these developed methods are vulnerable to both noise, interference and column coherence of training signal matrix. In other words, the primary objective of these conventional methods is to catch the dominant channel taps without a report of posterior channel uncertainty. To improve the estimation performance, we proposed a Bayesian sparse channel estimation (BSCE) method which not only exploits the channel sparsity but also mitigates the unexpected channel uncertainty. The proposed method can reveal potential ambiguity among multiple channel estimators that are ambiguous due to observation noise or correlation interference among columns in the training matrix. Computer simulations show that our technique can improve the estimation performance with comparable computational complexity when comparing with conventional SCE methods.

Accurate channel impulse response (CIR) is required for coherent detection and it also helps to improve the quality of service in next-generation wireless communication systems. Linear channel estimation methods, e.g., least square (LS), have been proposed to estimate the CIR. However, these methods never take advantage of the channel sparsity and they also cause performance loss. In this paper, we propose a sparse channel estimation method for multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) amplify and forward two-way relay networks (AF-TWRN), to exploit the sparse structure information in the CIR for each user. Sparse channel estimation problem is formulated as compressed sensing (CS) using sparse decomposition theory and the estimation process is implemented by LASSO algorithm. Computer simulation results are given to confirm the superiority of the proposed method over the LS-based channel estimation.

The well-known scheduling algorithms are Max-map, Max-Min, and Proportional fairness (PF)-map. Using the above scheduling algorithms, the capacity and the fairness among users vary according to the channel variation. Flexible system design is possible if the sum capacity and the fairness can be controllable. In this paper, assuming single-carrier frequency division multiple access (SC-FDMA) uplink, to control the trade-off between the capacity and the fairness among users, we present modified Max-map, Max-Min, and PF-map. We evaluate, by computer simulation, the sum capacity, the user capacity, and the fairness among users when using the modified scheduling algorithms. It is shown that the modified scheduling algorithms can control the trade-off relationship between the capacity and the fairness among users by changing the number of simultaneously accessing users.

In this paper, we propose a new broadband single-carrier (SC) multiple-input multiple-output (MIMO) transmission method to reduce the residual inter-antenna interference (IAI) and inter-symbol interference (ISI) after the minimum mean square error based receive filtering (Rx MMSE filtering). The proposed method jointly performs transmit and receive MMSE filtering (joint Tx/Rx MMSE filtering) to transform the MIMO channel to the orthogonal eigenmodes and allocate the transmit power based on MMSE criterion. Also, as the received signal-to-interference plus noise power ratio (SINR) of each eigenmode is significantly different, rank adaptation and adaptive modulation are jointly introduced to narrow the received SINR gap between each eigenmode. The superiority of the proposed method (adaptive SC-MIMO transmission using joint Tx/Rx MMSE filtering) is confirmed by computer simulation.

In single-carrier (SC) transmission with multiple receive-antennas, multi-user access can be realized by using interference suppression. In our previous study, SC frequency-domain adaptive antenna array (SC-FDAAA) transceiver was proposed to realize frequency domain interference suppression and it was proved that SC-FDAAA transceiver can accommodate up to the number-of-receive-antennas users. However, when the number of users is larger than the number of receiver antennas, the performance of SC-FDAAA receiver will be significantly degraded. In order to accommodate a larger number of users than the number of receive antennas, an SC-adaptive transceiver is proposed in this study based on non-orthogonal frequency allocation and frequency-domain interference suppression. The effectiveness of the proposed transceiver is shown by simulation results.

Frequency domain adaptive antenna array (FDAAA) was proposed in our previous study and was proved to be an effective method to suppress interference caused by frequency selective fading and multiple access interference (MAI) in single-carrier (SC) transmission. The performance of FDAAA receiver will be affected by the antenna placement parameters such as antenna separation and spread of angle-of-arrival (AOA) of resolvable paths. In this paper, we analyze the impact of antenna separation and AOA spread on the radiation pattern of FDAAA receiver and shows the effects of two important parameters: antenna separation and AOA spread.

Orthogonal frequency division multiplexing (OFDM) has been attracting much attention due to the robustness against the frequency selective fading. Instead of well-known cyclic prefix (CP) insertion, a known training sequence (TS) insertion can also be used for OFDM block transmission. In this paper, we propose a new receiver design, which can obtain the frequency diversity gain through the use of frequency-domain equalization (FDE), for TS-OFDM. The conditional bit error rate (BER) analysis of the proposed FDE is presented. The average BER performance of the TS-OFDM signal transmission in a frequency-selective Rayleigh fading channel is evaluated by Monte-Carlo numerical computation method using the derived conditional BER and is confirmed by computer simulation. Numerical results show the proposed TS-OFDM receiver improves BER and throughput performances of TS-OFDM compared to the conventional TS-OFDM receiver. It was also shown that the TS-OFDM with the proposed receiver provides better BER and throughput performances than the CP-OFDM due to the frequency diversity gain.

Least mean square (LMS) based adaptive algorithms have been attracted much attention since their low computational complexity and robust recovery capability. To exploit the channel sparsity, LMS-based adaptive sparse channel estimation methods, e.g., zero-attracting LMS (ZA-LMS), reweighted zero-attracting LMS (RZA-LMS) and Lp- norm sparse LMS (LP-LMS), have also been proposed. To take full advantage of channel sparsity, in this paper, we propose several improved adaptive sparse channel estimation methods using Lp-norm normalized LMS (LP-NLMS) and L0-norm normalized LMS (L0-NLMS). Comparing with previous methods, effectiveness of the proposed methods is confirmed by computer simulations.

The articles in this special issue focus on the technology and applications supported by virtual multiple antennas, or VMIMOs. The impetus for this has been spurred by the strong desire to understand VMIMO, which is a rapidly growing research area. VMIMO is believed to be a key technology for beyond 4th generation mobile communications technologies (B4G). It enables one to make use of all the neighboring terminals and amortize the cost of multiple antennas; hence, a large MIMO channel can be created to increase capacity significantly as well as improve error rate performance. Nevertheless, fundamental roadblocks need to be addressed in order to take full advantage of VMIMO.

Rateless codes have been found to be particularly attractive for decode and forward based relaying strategy in delay tolerant multihop networks. The latency performance of such networks is dependent on the worst links that results in the starvation of subsequent nodes with good channel conditions. The total delay suffered by such networks can be constrained by limiting the number of rateless coded transmissions, especially for applications with critical latency requirements. However, the performance of rateless codes deteriorates in such circumstances due to the lack of sufficient mutual information for successfully recovering the entire source packets. The fraction of source packets that can be recovered will depend on the encoded packets received across the transmission channel. This paper investigates the degradation in the performance of such rateless coded networks by deriving the average packet recovery rate. In order to improve the reliability in such delay constrained networks, a novel spectrally efficient transmission scheme for reliable multihop data transfer is proposed. The proposed scheme exploits the broadcast nature of wireless transmissions, which provides an inherent implicit feedback channel, to ensure the reliable delivery of information packets to the nodes in the network. Rather than allocating dedicated channels to feedback the packet recovery information, the implicit feedback channel determines such information which enhances the spectral efficiency. Further, the optimum number of packets recoverable within the specified delay constraint to reduce the reprocessing of lost packets across hops is analytically analysed in this paper.

Single-carrier transmission is a promising transmission technique due to its low peak-to-average power ratio (PAPR) property compared to multicarrier transmission, and using frequency-domain equalization (FDE) at the receiving side also mitigate the adverse effect of channel frequency-selectivity. An introduction of transmit filter can improve the system performance in terms of either PAPR or error probability. In this paper, we focus on the transmit filter aiming to reduce PAPR by employing the minimization of variance of instantaneous transmit power. Filter roll-off factor is also considered in order to provide excess-bandwidth transmission. With a combination of an FDE and spectrum combining at the receiver, excess-bandwidth transmission inherits additional frequency diversity gain, and therefore improves error probability. Performance evaluation of the proposed filtering algorithm is done by computer simulation, while the PAPR and bit-error rate (BER) performance of proposed algorithm are compared with conventional square-root Nyquist filter.

Accurate channel state information (CSI) is necessary for coherent detection in amplify and forward (AF) broadband cooperative communication systems. Based on the assumption of ordinary sparse channel, efficient sparse channel estimation methods have been investigated in our previous works. However, when the cooperative channel exhibits partial sparse structure rather than ordinary sparsity, our previous method cannot take advantage of the prior information. In this paper, we propose an improved channel estimation method with partial sparse constraint on cooperative channel. At first, we formulate channel estimation as a compressive sensing problem and utilize sparse decomposition theory. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over ordinary sparse channel estimation methods.

An introduction of the adaptive modulation improves the throughput of a 2-time slot cooperative relay. The throughput depends on conditions of mobile terminal (MT)-base station (BS) link, MT-relay station (RS) link, and RS-BS link. However, the cooperative relay is effective when the MT-BS direct link quality is worse than the others. Therefore, the best modulation combination can be chosen using instantaneous CSIs of MT-RS link and RS-BS link In this paper, by neglecting the MT-BS direct link contribution, we introduce an adaptive modulation using instantaneous channel state information (CSI) of MT-RS link and RS-BS link. We evaluate, by computer simulation, the throughput performance of single-carrier (SC) 2-time slot cooperative decode-and-forward (DF) relay using adaptive modulation. It is shown that the introduction of adaptive modulation can reduce by about 1.8 dB the required transmit power for achieving a 1%-outage throughput of 1.4 bps/Hz compared to the conventional method.

Global roaming and high-quality wireless communication, is now becoming a reality. This is mainly due to recent technological advances in wireless communications which consist of a wide range of technologies and applications to fulfill the particular needs of end-users in different deployment scenarios (Bluetooth, Wi-Fi, WiMAX, and 3G/4G cellular systems). In such a heterogeneous wireless environment, one of the key ingredients to provide efficient ubiquitous computing is the design of intelligent handoff algorithms which select the optimal target network. This paper presents a novel approach for the design and implementation of a multi-criteria vertical handoff decision algorithm for heterogeneous wireless networks to achieve seamless mobility while maximizing end-users' satisfaction. A weighting scheme is first proposed for the system parameters and consequently, two important modules are proposed. The first module estimates the necessity of handoffs and the other module selects the best network for future connection using a FTOPSIS ranking algorithm. Performance of our scheme is illustrated by an exemplary deployment scenario and also by simulating a practical heterogeneous wireless environment for a single user scenario.

QR decomposition based near maximum likelihood (ML) block detection significantly improves the transmission performance of uplink single-carrier (SC) multi-user multiple-input multiple-output (MU-MIMO). Hybrid automatic repeat request (HARQ) is an indispensable error control technique for high quality packet data transmission. The achievable diversity gain of HARQ depends on the packet combining strategy. In uplink MU-MIMO HARQ, received signal may consist of new packets and retransmitted packets as retransmission for each user acts independently. In this paper, a recursive QR packet combining scheme suitable for uplink SC MU-MIMO HARQ is proposed, which takes into account the number of retransmissions for each user in the detection order. The proposed scheme helps reduce the computational complexity and storage requirement significantly. Moreover, it improves the packet error rate (PER) performance significantly over the conventional bit-level log likelihood ratio (LLR) packet combining, as shown by our computer simulation results.

In a highly integrated ubiquitous wireless environment, the selection of a network that can fulfill end-users' service requests while keeping their overall satisfaction at a high level, is vital. The wrong selection can lead to undesirable conditions such as unsatisfied users, weak Quality of Service (QoS), network congestions, dropped and/or blocked calls, and wastage of valuable network resources. The selection of these networks is performed during the handoff process when a Mobile Station (MS) switches its current Point of Attachment (PoA) to a different network due to the degradation or complete loss of signal and/or deterioration of the provided QoS. Traditional schemes perform the handoff necessity estimation and trigger the network selection process based on a single metric such as Received Signal Strength (RSS). These schemes are not efficient enough, as they do not take into consideration the traffic characteristics, user preferences, network conditions and other important system metrics. This paper presents a novel multi-attribute vertical handoff algorithm for heterogeneous wireless networks which achieves seamless mobility while maximizing end-users' satisfaction. Two modules are designed to estimate the necessity of handoff and to select the target network. These modules utilize parallel Fuzzy Logic Controllers (FLCs) with reduced rule-set in combination with a network ranking algorithm developed based on Fuzzy VIKOR (FVIKOR).

Coherent detection and demodulation at the receiver requires channel state information (CSI). We investigate channel estimation problem in sparse multipath non-orthogonal amplify-and- forward (NAF) cooperative networks. Traditional linear estimation methods can obtain lower bound at the cost of spectrum efficiency which is becoming more and more scarcity. In this paper, system model is described from sparse representation perspective. Based on the compressed sensing theory, we propose several compressed channel estimation methods to exploit sparsity of the cooperative channels. Simulation results confirm the superiority of proposed methods than LS-based linear estimation method.

Multiple-input multiple-output (MIMO) spatial multiplexing is known to increase the transmission rate without bandwidth expansion. However, in cellular networks (CNs), the transmission rate of a user close to the cell edge significantly degrades because the received signal-to-interference plus noise power ratio (SINR) degrades due to the presence of strong co-channel interference (CCI) from neighboring cells. Distributed antenna network (DAN), in which many antennas are spatially distributed over the cell, is suitable for MIMO spatial multiplexing because the received SINR improves over the entire cell. In this paper, assuming block transmission with cyclic prefix (CP) insertion, we theoretically derive an expression for the downlink spectral efficiency of DAN-MIMO spatial multiplexing in a multi-cell environment. Then, we propose the optimal and suboptimal transmit power allocation schemes for DAN-MIMO spatial multiplexing. We evaluate the spectral efficiency distribution by Monte Carlo numerical computation method to show that DAN allows single frequency reuse and achieves higher spectral efficiency compared to CN.

In this paper, we propose a dynamic channel assignment (DCA) scheme for distributed antenna networks (DANs). DANs, in which many antennas are distributed in each cell, significantly reduce the transmit power compared to conventional cellular networks (CNs). In DAN, a different group of channels should be assigned for each distributed antenna to avoid the interference. Since DAN can also reduce the interference power due to its low transmit power property, the same channel groups can be reused even within the same cell. Proposed DCA scheme dynamically assigns the channels based on the co-channel interference measurement. Computer simulation results demonstrate that the DAN using proposed DCA achieves higher spectrum efficiency than the conventional CN.

In this paper, we propose a joint transmit/receive frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion for multi-input multi-output (MIMO) analog network coding (ANC) in single-carrier (SC) bi-directional relay communications. In the proposed scheme, the relay station (RS) equipped with multiple antennas carries out antenna diversity and one-tap transmit FDE, and the base station (BS) and mobile terminal (MT) receivers, both equipped with single antenna, carry out one-tap receive FDE only. The FDE weights at RS, BS and MT are jointly optimized so as to minimize the end-to-end mean square error (MSE). We evaluate, by computer simulations, the bit error rate (BER) performance when using the proposed scheme, and discuss how the transmit FDE at RS operates and affects the BER performance.

A block signal maximum likelihood detection (MLD) employing QR decomposition and M-algorithm (QRM-MLBD) can significantly improve the bit error rate (BER) performance of the single carrier (SC) transmissions in a frequency-selective fading channel, compared to the conventional frequency-domain equalization (FDE). In QRM-MLBD, the cyclic prefix (CP) is inserted in order to avoid inter-block interference (IBI). However, the CP insertion reduces the transmission efficiency. In this paper, we propose an overlap QRM-MLBD which requires no CP insertion. In overlap QRM-MLBD, IBI can be suppressed by overlapping consecutive observation windows and picking up only the reliable part after the block signal detection. We evaluate the average BER performance and the throughput performance by computer simulation to compare with the conventional QRM-MLBD with CP insertion.

A time-domain maximum likelihood block signal detection employing QR decomposition and M-algorithm (TD-QRM-MLBD) is a computationally efficient near ML detection scheme and can significantly improve the bit error rate (BER) performance of the single-carrier (SC) transmissions in a frequency-selective fading channel, compared to the conventional minimum mean square error based frequency-domain equalization (MMSE-FDE). In TD-QRM-MLBD, the cyclic prefix (CP) is inserted in order to avoid inter-block interference (IBI). However, the CP insertion reduces the transmission efficiency. In this paper, we propose an iterative overlap TD-QRM-MLBD which requires no CP insertion. We evaluate the throughput performance of iterative overlap TD-QRM-MLBD by computer simulation to compare it with the conventional TD-QRM-MLBD with CP insertion.

In this paper, we propose a power allocation method for the direct/cooperative amplify-and-forward (AF) relay switched SC-FDMA using spectrum division/adaptive subcarrier allocation (SDASA). The cooperative relaying is used only when it can achieve higher channel capacity than the direct communication. In the proposed power allocation method, transmit power is adaptively allocated to mobile terminal (MT) and relay station (RS) according to the channel conditions of MT-RS link and RS-base station (BS) link when the use of cooperative relay is selected. We evaluate the achievable channel capacity of the proposed power allocation method by Monte-Carlo numerical computation method. It is shown that the proposed power allocation method can achieve almost the same channel capacity as the grid search method.

In this paper, frequency-domain one-tap weight control for single-carrier multiple access with multiple antennas is considered. Adaptive antenna array (AAA) weight control, diversity combining (DC) weight control and least square (LS) weight control are studied. These three weight control algorithms belong to multiple-input multiple-output (MIMO) beam forming, MIMO diversity and MIMO multiplexing, respectively. The weight control algorithms will be evaluated and compared in terms of computational complexity as well as bit error rate (BER) performance in a frequency-selective Rayleigh fading channel.

2-step maximum likelihood block signal detection employing QR decomposition and M-algorithm (QRM-MLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while reducing the computational complexity compared to maximum likelihood detection (MLD). In 2-step QRM-MLBD, unreliable symbol candidates are removed by performing minimum mean square error based frequency-domain equalization (MMSE-FDE) prior to QRM-MLBD. However, a large number M of surviving paths is still required in the M-algorithm to achieve a BER performance close to the matched filter (MF) bound. In this paper, to remedy this problem, we introduce a detection ordering to 2-step QRM-MLBD. We will show by computer simulation that the use of detection ordering can achieve the same BER performance as 2-step QRM-MLBD while reducing the computational complexity.

For high-speed packet access, hybrid automatic repeat request (HARQ) and multi-input multi-output (MIMO) multiplexing are indispensable techniques. Single-carrier (SC) MIMO block transmission using frequency-domain signal detection such as the frequency-domain linear detection based on the minimum mean square error criterion (MMSED) can improve the HARQ throughput performance over the frequency-selective fading channel. However, the performance improvement is limited due to not only an inter-antenna interference (IAI) but also an inter-symbol interference (ISI) resulting from a severe frequency-selective fading. In this paper, we propose to jointly use a training sequence (TS) aided SC block transmission and a near maximum likelihood (ML) block detection using QR decomposition and M-algorithm (QRM-MLBD) for SC-MIMO HARQ. It is shown, by computer simulation, that SC-MIMO using TS aided QRM-MLBD significantly improves the HARQ throughput performance compared to an often used cyclic prefix (CP) inserted SC-MIMO while significantly reducing the computational complexity. It is also shown that proposed TS aided QRM-MLBD achieves a significantly higher throughput than the MMSED particularly when higher level modulation is used.

In this paper, we propose a 2-step frequency-domain channel estimation scheme suitable for training sequence inserted single-carrier (TS-SC) block transmission using frequency-domain equalization (FDE). In the first step, the received training sequence having cyclic property is constructed for frequency-domain channel estimation to obtain the instantaneous channel estimate. Improved channel estimate is obtained by simply averaging the instantaneous channel estimates over several blocks. In the second step, the maximum likelihood channel estimation is carried out iteratively by using both the estimated symbol sequence and the training sequence. The BER performance with the proposed frequency-domain channel estimation scheme is evaluated by computer simulation. It is shown that the proposed channel estimation scheme achieves a BER performance close to the perfect channel estimation.

In order to provide an increased capacity for voice users in emergency scenarios, a low-medium-altitude aerial platform based time-division-duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Furthermore, a novel radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game to provide real-time voice communications with as many users as possible. Our simulation results demonstrate that compared with the traditional radio resource management algorithms, the proposed algorithm achieves the largest capacity, i.e., the number of serviced users.

In broadband DS-CDMA uplink transmission using frequency-domain equalization (FDE) without cyclic prefix (CP) insertion, the transmission performance degrades due to inter block interference (IBI) and circular property loss. In this paper, IBI cancellation and circular property restoration is proposed and the performance improvement is evaluated by computer simulation. It is shown that IBI cancellation & circular property restoration can improve the bit error rate (BER) performance in a frequency-selective Rayleigh fading channel. It is also shown that circular property restoration is more powerful than the IBI cancellation.

Cooperation among nodes is proposed as an effective means of combating fading and for enhancing system's overall capacity and coverage. The robustness of rateless codes makes them particularly attractive for such networks. Yet, the decoding aspects of rateless codes are discarded in most of the traditional distributed networks. In this paper, the intermediate packet decodability of rateless codes is exploited to reduce the number of packets being processed at the relay nodes. This is achieved by harnessing the back channel (from destination to relays) for feedback. The relay transmissions and processing are thereby confined to assist the receiver in decoding the remaining information. It is shown both analytically and through simulation studies that such a scheme achieves significant savings in computation complexity, memory usage and overall energy consumption.

The 15 papers in this special issue are divided into four categories: challenges in broadband wireless communications; physical layer techniques; radio resource management techniques; and field measurement and channel modeling.

Broadcast nature of the wireless channel enables wireless communications to make use of network coding at the physical layer (PNC) to improve the network capacity. Recently, narrowband and later broadband analog network coding (ANC) were introduced as a simpler implementation of PNC. The ANC schemes require two time slots while in PNC three time slots are required for bi-directional communication between two nodes and hence ANC is more spectrum efficient. The coherent detection and self-information removal in ANC require accurate channel state information (CSI). {In this paper, we theoretically analyze the bit error rate (BER) performance with imperfect knowledge of CSI for broadband ANC using orthogonal frequency division multiplexing (OFDM), where the channel estimation error is modeled as a zero-mean complex Gaussian random variable. We investigate the BER performance for three cases: (i) the effect of imperfect self-information removal due to channel estimation (CE) error with fading tracking errors, (ii) the effect of imperfect self-information removal due to CE error without fading tracking errors}, and (iii) the ideal CE case. We discuss how, and by how much, our results obtained by theoretical analysis can be used for design of broadband ANC system with the imperfect knowledge of CSI. Our results show that imperfect channel estimation due to the noise effect has less impact on self-information removal than the imperfect channel estimation due to fading tracking errors. The tracking against fading is an important problem for accurate self-information removal as well as coherent detection and thus, the effect of channel time-selectivity is also theoretically studied. The achievable BER performance gains due to the polynomial time-domain channel interpolation are investigated using the derived close-form BER expressions and it was shown that the broadband ANC schemes with practical CE in a time- and frequency-selective channel should include a more sophisticated channel interpolation techniques since the impact of Doppler shift has prevalent effect on the achievable BER performance.

ABSTRACT Orthogonal frequency division multiplexing (OFDM) signals have a problem with a high peak‐to‐average power ratio (PAPR). A distortionless selected mapping (SLM) has been proposed to reduce the PAPR, but a high computational complexity prohibits its application to an OFDM system with a large number of subcarriers. Recently, we proposed OFDM combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency‐domain equalization (MMSE‐FDE) to improve the bit error rate (BER) performance of conventional OFDM with a lower PAPR. The PAPR problem, however, cannot be completely eliminated. In this paper, we present an SLM combined with symbol re‐mapping for OFDM/TDM using MMSE‐FDE. Unlike the conventional OFDM, where SLM is applied over subcarriers in the frequency domain, we exploit both time and frequency dimensions of OFDM/TDM signal to improve the performance with respect to PAPR and BER. A mathematical model for PAPR distribution of OFDM/TDM with SLM is presented to complement the computer simulation results. It is shown that proposed SLM can further reduce the PAPR without sacrificing the BER performance with the same or reduced computational complexity. Copyright © 2010 John Wiley & Sons, Ltd.

ABSTRACT Orthogonal frequency division multiplexing (OFDM) has been adopted for several wireless network standards due to its robustness against multipath fading. Main drawback of OFDM is its high peak‐to‐average power ratio (PAPR) that causes a signal degradation in a peak‐limiting (e.g., clipping) channel leading to a higher bit error rate (BER). At the receiver end, the effect of peak limitation can be removed to some extent to improve the system performance. In this paper, a joint iterative channel estimation/equalization and clipping noise reduction technique based on minimum mean square error (MMSE) criterion is presented. The equalization weight that minimizes the mean square error (MSE) between the signal after channel equalization and feedback signal after clipping noise reduction is derived assuming imperfect channel state information (CSI). The MSE performance of the proposed technique is theoretically evaluated. It is shown that the BER performance of OFDM with proposed technique can be significantly improved in a peak‐limited and doubly‐selective (i.e., time‐ and frequency‐selective) fading channel. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT QR decomposition‐based near maximum likelihood block detection significantly improves the transmission performance of uplink single‐carrier (SC) multi‐user multiple‐input multiple‐output (MU‐MIMO). Hybrid automatic repeat request (HARQ) is an indispensable error control technique for high‐quality packet data transmission. The achievable diversity gain of HARQ depends on the packet combining strategy. In uplink MU‐MIMO HARQ, the received signal may consist of new packets and retransmitted packets as retransmission for each user acts independently. In this paper, a recursive QR packet combining scheme suitable for uplink SC MU‐MIMO HARQ is proposed, which takes into account the number of retransmissions for each user in the detection order. The computational complexity and required storage size can be significantly reduced by the proposed scheme. Moreover, it improves the packet error rate performance and throughput performance significantly over the conventional bit‐level log likelihood ratio packet combining, as shown by our computer simulation results. Copyright © 2012 John Wiley & Sons, Ltd.

Future wireless Internet services require a broadband frequency spectrum with high data rates. Cognitive radio (CR) concept is a novel approach to improve the spectrum efficiency. The CR is based on the opportunistic usage of frequency spectrum, which is not occupied by the primary users. Conventional multi-user access in bi-directional CR network may be done by using either time division multiple access (TDMA), frequency division multiple access (FDMA) or code division multiple access (CDMA). Without adaptive or dynamic frequency reuse, TDMA and FDMA have lower spectrum efficiency in comparison with CDMA. However, the problem of CDMA in a multipath channel is a multi-user interference (MUI). In this paper, we present a bi-directional CR network with wireless network coding (WNC) in a multipath channel. Unlike the conventional multi-user bi-directional CR network, where the users access the spectrum holes in different time-slot or frequency, the proposed method allows secondary users (SUs) to access the spectrum holes simultaneously. The performance of bi-directional CR network with WNC is theoretically analyzed in terms of spectrum efficiency and the maximum number of SUs. The numerical results show that the spectrum efficiency and the maximum number of SUs of the proposed method increases in comparison with conventional CR network.

Cooperative transmission, where spatially distributed users form a multi-antenna system and assist in forwarding the information from source to destination node, achieves the diversity gain of a multiple-input multiple-output (MIMO) system. Cooperative network based on OFDM has been proposed to cope with the channel frequency-selectivity but due to high peak-to-average power ratio (PAPR) of OFDM, expensive power amplifier are required. In this paper, we present cooperative network based on OFDM combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency-domain equalization (MMSE-FDE) in a frequency-selective fading channel. We theoretically analyze the network performance with respect to the bit error rate (BER). The conditional signal-to-interference plus noise ratio (SINR) expressions are derived based on Gaussian approximation of the residual inter-slot interference (ISI) after MMSE-FDE for the given set of channel gains. The average BER performance for OFDM/TDM is evaluated by Monte-Carlo numerical computation method using the derived theoretical expressions and confirmed by computer simulation. The results show that the lower BER is achieved with cooperative OFDM/TDM in comparison with OFDM based cooperative network because OFDM/TDM exploits both cooperative and frequency diversity gains.

Overlap frequency-domain equalization (FDE) requires no cyclic prefix (CP) insertion. In this paper, a new minimum mean square error (MMSE) weight is derived for the overlap FDE. In the previous paper, the MMSE weight for overlap FDE is derived by approximating the IBI as a white Gaussian variable. However, the IBI is an independent colored noise. We derive a new MMSE weight by taking into account this fact. We evaluate the bit error rate (BER) performance by computer simulation, and show that overlap FDE using the newly derived MMSE weight reduces the residual inter-symbol interference (ISI) more and hence, improves the BER performance.

Broadband analog network coding (ANC) has been recently introduced to increase the network capacity by exploiting the broadcasting nature of the wireless channel. However, channel state information (CSI) knowledge is required for self-information removal and signal detection. Recently, a pilot-assisted channel estimation (PACE) scheme has been presented for broadband ANC, where feedback of the channel estimates from the relay to the users is required. In this work, we introduce a PACE scheme without feedback from the relay for broadband ANC using orthogonal frequency-division multiplexing (OFDM). In the first time slot the users transmit their respective pilots to the relay and in the second time slot the relay simply amplifies and forwards the received pilot signals to both users. Each user can then estimate all the CSI it needs for self-information removal and coherent signal detection, without requiring any feedback from the relay. The bit error rate (BER) performance of broadband ANC using the proposed PACE is evaluated by computer simulation. It was shown that the proposed PACE scheme causes only a slight BER performance degradation compared to the conventional PACE scheme while eliminating the feedback channel requirement.

For high-speed packet access, hybrid automatic repeat request (HARQ) and multiple-input multiple-output (MIMO) multiplexing are indispensable techniques. As the multiple-access technique, single carrier (SC)-frequency-division multiple-access (FDMA) using transmit filtering is promising. The use of square root Nyquist transmit filter reduces peak-to-average power ratio (PAPR) of the transmit SC-FDMA signal and increases the frequency diversity gain. However, if the carrier-frequency separation among multiple-access users is kept the same as in the case of the transmit filter's roll-off factor α=0 (i.e., brick wall filter), the adjacent users' signal spectra overlap and the multi-user interference (MUI) is produced. In this paper, we propose an iterative minimum mean square error signal detection and interference cancellation (MMSED-IC) for turbo coded uplink SC FDMA MIMO using HARQ. In the proposed MMSED-IC, not only the inter-antenna interference (IAI) and residual inter-symbol interference (ISI) but also MUI are cancelled in an iterative fashion. We evaluate the HARQ throughput performances by computer simulation, and show that the use of roll-off factor α=1 achieves the highest throughput performance.

Wireless sensor networks have been attracting a great attention due to their wide range of potential applications. However, due to various limitations arising from their inexpensive nature, limited size, weight and ad hoc method of deployment, the power consumption is one of the major constraints in sensor networks. Moreover, it is well known that packet communication dominates the power consumption in wireless sensor network. Therefore, it is very desirable to reduce the amount of packet transmission as much as possible. Network coding can achieve this by improving network throughput. Thus, recently researchers have been emphasizing on how wireless sensor networks can get benefits from network coding. AdapCode is one of the available works which apply the practical network coding to the wireless sensor networks. However, AdapCode has some limitations. It cannot find out all actual neighbour nodes which is critical in determining the new coding scheme. In this paper, thus, we enhance the AdapCode by deploying the power efficient neighbour discovery protocol to find out all the neighbours. Our objective is to develop a data dissemination protocol that promises the full advantage of network coding by deploying the power efficient neighbour discovery protocol.

QR decomposition with M-algorithm maximum likelihood detection (QRM-MLD) block signal detection can significantly improve the packet error rate (PER) performance of cyclic prefix-inserted single-carrier (CP-SC) multi-input multi-output (MIMO) spatial multiplexing when compared to the frequency-domain spatial filtering based on the minimum mean square error (MMSE) criterion. However, in order to achieve the sufficiently improved performance, the use of a fairly large number M of surviving paths in the M-algorithm is required because if smaller M is used, the probability of removing the correct path at early stages increases. In this paper, to reduce this probability, we proposed a training sequence-aided QRM-MLD block signal detection for SC MIMO spatial multiplexing. We show by computer simulation that training sequence-aided SC (TA-SC) MIMO spatial multiplexing using QRM-MLD block signal detection with M=16 can achieve the PER performance similar to CP-SC MIMO spatial multiplexing with M=1024 in the case of 16QAM and 4×4 MIMO spatial multiplexing.

For the realization of future wireless networks, gigabit wireless technology which can achieve higher-than-1Gbps data transmission with extremely low transmit power is indispensable. We have been studying the distributed antenna network (DAN) and the frequency-domain wireless signal processing. In DAN, many antennas or clusters of antennas are spatially distributed over a service area and they are connected by means of optical fiber links with DAN signal processing center (SPC). A number of distributed antennas cooperatively serve mobile users using spatial multiplexing, diversity, array or relaying technique. In this paper, the recent research advances of gigabit DAN and its related wireless techniques are introduced.

Network coding at the physical layer (PNC) can be used to improve the network capacity in a wireless channel. Broadband analog network coding (ANC) was introduced as a simpler implementation of PNC. The coherent detection and self-information removal in ANC require accurate channel state information (CSI). In this paper, we theoretically investigate an impact of the channel time-selectivity on the bit error rate (BER) performance of broadband ANC with practical channel estimation (CE) scheme using orthogonal frequency division multiplexing (OFDM). The achievable BER performance gains due to the first and second order polynomial time-domain channel interpolation are evaluated using derived close-form BER expressions.

In this paper, we investigate how a distributed antenna network (DAN) offers better throughput performance than a conventional cellular network (CN). In DAN, a group of multiple antennas are distributed in each cell of the CN in order to mitigate the adverse effect of path loss. Moreover, antenna diversity technique can make use of shadowing and multipath fading to improve the transmission performance due to a large spatial diversity gain. In this paper, we consider frequency-domain space-time block coded-joint transmit/ receive diversity (FD-STBC-JTRD) for downlink transmission of single-carrier (SC) DAN. FD-STBC-JTRD uses frequency-domain pre-equalization (pre-FDE) instead of receive FDE to keep the mobile terminal's complexity low, and achieves the full-diversity gain. We show by computer simulation that the transmit power for achieving the required throughput can be significantly reduced compared to the conventional CN.

Several attractive features of ultra wideband (UWB) communications make it a good candidate for physical-layer of wireless sensor networks (WSN). These features include low power consumption, low complexity and low cost of implementation. In this paper, we present an opportunistic power assignment strategy for distributed detection in parallel fusion WSNs, considering a Nakagami-m fading model for the communication channel and time-hopping (TH) UWB for the transmitter circuit of the sensor nodes. In a parallel fusion WSN, local decisions are made by local sensors and transmitted through wireless channels to a fusion center. The fusion center processes the information and makes the final decision. Simulation results are provided for the global probability of detection error and relative performance gain to evaluate the efficiency of the proposed power assignment strategy in different fading environments.

This paper studies the multi-user downlink transmit beamforming algorithms for the broadband single-carrier distributed antenna network (SC-DAN). The distributed antennas will be used as antenna arrays by using transmit beamforming. In this work, the beamforming weight is designed in order to avoid the interference cancellation from the mobile terminals. Two methods are adopted. One is to use the maximum ratio transmission (MRT) beamforming weight to maximize the desired signal's power at each mobile terminal. The other one is to use the null steering beamforming weight to minimize the interference power at each mobile terminal. The beamforming algorithms using the two methods are described and their performances are compared by computer simulations.

Uplink multi-user direct sequence-code division multi-access (DS-CDMA) suffers from strong multi-user interference (MUI) and self inter-chip interference (ICI) caused by severe frequency-selective fading. In this paper, we propose a joint Tx/iterative Rx frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion and successive MUI cancellation (MUIC) for DS-CDMA uplink. In the proposed scheme, each user applies one-tap Tx FDE before transmitting signal. At the base station, joint one-tap Rx FDE and successive MUIC is iteratively performed. The FDE weights of users and base station are jointly optimized based on the MMSE criterion in order to reduce MUI and ICI while exploiting channel frequency-selectivity. Computer simulation results show that the proposed scheme provides much improved bit error rate (BER) performance than the conventional iterative Rx MMSE-FDE with successive MUIC.

We propose an incremental relaying scheme using joint Tx/Rx frequency-domain equalization (FDE) for single-carrier (SC) transmission. If a packet sent by a source node (S) has been correctly decoded at a relay node (R), but not at the destination node (D), retransmission is cooperatively done by S and R. Assuming that the channel state information (CSI) is shared by S, R, and D, joint Tx/Rx FDE is performed. We derive a set of optimal/suboptimal Tx/Rx FDE weights among S, R, and D, based on the minimum mean square error (MMSE) criterion under total transmit power constraint of S and R. Computer simulation verifies the effectiveness of the proposed scheme.

A new 2-step maximum likelihood block signal detection employing QR decomposition and M-algorithm (QRM-MLBD) is proposed to further reduce the computational complexity while keeping a good bit error rate (BER) performance for the single-carrier (SC) transmission in a frequency-selective fading channel. Prior to QRM-MLBD, a computationally efficient minimum mean square error based frequency-domain equalization (MMSE-FDE) is performed to discard the symbol candidates in the tree based on the soft decision results of MMSE-FDE. We evaluate, by computer simulation, the BER performance achievable by the proposed improved 2-step QRM-MLBD and show that the proposed scheme can reduce the computational complexity compared to the previously proposed conventional 2-step QRM-MLBD while keeping the same BER performance.

In this paper, we present an analytical framework to design system parameters for load-balancing multiuser spectrum decision schemes in cognitive radio (CR) networks. Unlike the non-load-balancing methods that multiple secondary users may contend for the same channel, the considered load-balancing schemes can distribute the traffic loads of secondary users to multiple channels. Based on the preemptive resume priority (PRP) M/G/1 queueing theory, a spectrum decision analytical model is proposed to evaluate the effects of multiple interruptions from the primary user during each link connection, the sensing errors (i.e., missed detection and false alarm) of the secondary users, and the heterogeneous channel capacity. With the objective of minimizing the overall system time of the secondary users, we derive the optimal number of candidate channels and the optimal channel selection probability for the sensing-based and the probability-based spectrum decision schemes, respectively. We find that the probability-based scheme can yield a shorter overall system time compared to the sensing-based scheme when the traffic loads of the secondary users is light, whereas the sensing-based scheme performs better in the condition of heavy traffic loads. If the secondary users can intelligently adopt the best spectrum decision scheme according to sensing time and traffic conditions, the overall system time can be improved by 50% compared to the existing methods.

ABSTRACT For the realization of future wireless networks, gigabit wireless technology, which can achieve higher‐than‐1 Gbps data transmission with extremely low transmit power, is indispensable. We have been studying the distributed antenna network (DAN) and the frequency domain wireless signal processing. In DAN, many antennas or clusters of antennas are spatially distributed over a service area, and they are connected by means of optical fiber links with DAN signal processing center. A number of distributed antennas cooperatively serve mobile users using spatial multiplexing, diversity, array, or relaying technique. In this paper, the recent advances in single‐carrier DAN are introduced. Copyright © 2011 John Wiley & Sons, Ltd.

This paper investigates how to characterize the effect of multiple spectrum handoff delay on the extended data delivery time of the secondary users' connections in cognitive radio (CR) networks. Whenever a primary user appears, the spectrum handoff procedures are initiated for the interrupted secondary users. Through spectrum sensing, the secondary user can reactively decide the target channel for spectrum handoff to resume its unfinished transmission. Clearly, many interruptions from the primary users will result in multiple handoffs, thereby increase the extended data delivery time of a secondary connection. In this paper, we develop a Markov transition model integrating with the preemptive resume priority (PRP) M/G/1 queueing network to characterize the multiple handoff delay, resulting from the sensing time, the handshaking time, the channel switching time, and the waiting time. The analytical results can facilitate the designs of admission control rules for the secondary users subject to their latency requirements and provide a framework to determine whether the spectrum sensing technology can effectively shorten the extended data delivery time under various traffic arrival rates and service time as well as sensing time.

In this paper, we propose a new joint transmit/receive equalization technique for single-carrier (SC) block transmissions in a severe frequency-selective fading channel. An iterative frequency-domain inter-symbol interference cancellation (FDIC) is introduced to the joint transmit/receive (Tx/Rx) frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion which was previously proposed by authors. At a receiver, a 1-tap FDE and FDIC are jointly used and they are updated in an iterative manner to achieve larger frequency diversity gain. Since the transmit FDE weight cannot be updated, we introduce a virtual receiver having a receive FDE & FDIC into the transmitter. In the virtual receiver at the transmitter, the same degree of the residual ISI cancellation is assumed to compute the transmit FDE weight, based on the MMSE criterion, matched to the receive FDE & FDIC. The computer simulation results show that the bit error rate (BER) performance is significantly improved by using our proposed scheme.

In this paper, we consider user selection criteria for various multiple input multiple output (MIMO) detectors to exploit the multiuser diversity. It is shown that the user selection criterion plays a crucial role in exploiting both multiuser and receive (or spatial) diversity. We also show that the maximum likelihood (ML) and even some low complexity suboptimal detectors (based on the lattice reduction (LR)) can achieve a full multiuser and receive diversity when the user selection criterion is properly chosen.

In cellular systems, multi-user multi-input multi-output (MIMO) multiplexing can increase the number of simultaneous users per cell; however co-channel interference (CCI) from other cells limits the number of users/cell (defined as the cellular capacity). The well-known zero-forcing detection (ZFD) and minimum mean square error detection (MMSED) are computationally efficient detection methods, but their diversity order decreases as the number of users increases. The multi-user signal detection method which has the full diversity order and less complexity is required in order to enhance the cellular capacity. In this paper, we introduce the lattice reduction (LR) aided ZFD and MMSED to the uplink multi-user MIMO using orthogonal frequency division multiplexing (OFDM) and investigate the uplink cellular capacity. LR using Lenstra-Lenstra-Lovasz (LLL) algorithm is a promising technique to improve the performance of ZFD and MMSED. We show that LR aided ZFD and MMSED can obtain larger uplink capacity than conventional ZFD and MMSED at the cost of relatively low increase of computational complexity.

In this paper, a 2-dimensional water-filling (2D-WF) based transmit weight that maximizes the channel capacity is theoretically derived for the downlink transmit diversity of single-carrier distributed antenna network (SC DAN) in a frequency-selective channel. The 2D-WF transmit weight allocates the transmit power in both transmit antenna dimension and frequency dimension: power allocation across frequencies based on WF theory and across transmit antennas based on maximal ratio transmission (MRT). The cumulative distribution function (CDF) of the achievable channel capacity by 2D-WF transmit diversity is evaluated by the Monte-Carlo numerical computation method. Channel capacities achievable with 2D-WF, MRT, and 1D WF transmit weight are compared. It is shown that the 2D-WF transmit weight provides the highest channel capacity among three transmit weights.

Frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion is a promising equalization technique for the broadband single-carrier (SC) transmission. However, the presence of timing offset produces the inter-symbol interference (ISI) and degrades the bit error rate (BER) performance. As the roll-off factor of the transmit filter increases, the performance degradation gets larger. In this paper, we propose joint MMSE-FDE & spectrum combining which can achieve the frequency diversity gain while suppressing the negative impact of timing offset for the SC transmission.

Single carrier (SC) signal transmission has a property of low peak-to-average power ratio (PAPR) and achieves the frequency diversity gain by the use of frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion. In this paper, Nyquist filtered broadband SC transmission is considered. As the transmit filter roll-off factor α increases, the signal bandwidth increases and the PAPR reduces. MMSE-FDE using spectrum combining was proposed in [15]. An additional frequency diversity gain can be obtained by making use of the excess bandwidth introduced by the transmit filter and by using spectrum combining. In this paper, we thoroughly investigate how α affects PAPR, BER performance, and throughput performance.

The peak-to-average power ratio (PAPR) of Nyquist filtered broadband single carrier (SC)-FDMA signals can be reduced by increasing the filter roll-off factor α. Furthermore, an additional frequency diversity gain can be obtained by making use of the excess bandwidth introduced by the transmit filtering. However, if the carrier-frequency separation is kept the same as in the case of α=0, the adjacent users' signal spectra overlap with the desired users' spectrum and the multiuser interference (MUI) is produced. In this paper, in order to improve the transmission performance of uplink SC-FDMA using frequency-domain filtering, we propose two type of frequency-domain iterative MUI cancellation scheme which can achieve the frequency diversity gain through MMSE-FDE&spectrum combining. The achievable bit error rate (BER) and throughput performances are evaluated by computer simulation.

In this paper, a single-carrier frequency domain adaptive antenna array (FDAAA) is proposed for the uplink transmission in cellular systems. The FDAAA algorithm will deal with co-channel interference and exploit the frequency selectivity of the channel fading jointly by using adaptive antenna array in the frequency domain. The receiver of the base station (BS) needs to adjust the AAA weight to optimize the system performance. The conventional cellular structures using frequency reuse factors 1, 3, 4 and 7 are considered. The performance of the proposed algorithm is confirmed by simulations.

Recently, broadband analog network coding (ANC) was introduced to utilize high-data rate transmission over the wireless - frequency selective fading - channel. However, ANC requires the knowledge of channel state information (CSI) for self-information removal and coherent signal detection. In this paper, we propose a two-slot pilot-assisted CE for bi-directional broadband ANC. In the first slot, two users transmit their respective pilots to the relay, where the users' pilot signals are designed to avoid the interference and consequently, allow the relay to estimate the CSIs from both users. During the second slot the relay broadcast its pilot signal to both users that estimate the corresponding CSIs. It was shown by computer simulation that, even with imperfect CSI, the BER performance of broadband ANC gives a satisfactory performance for a low and moderate mobile terminal speed in a frequency-selective fading channel.

In the next generation high-speed wireless packet access systems, hybrid automatic repeat request (HARQ) is necessary to achieve higher throughput performance. An HARQ with Chase combining (CC) transmits the same coded packet until it is correctly received. The received packets are combined to achieve the time-diversity gain. Recently, we proposed a joint transmit/receive frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion for a broadband single-carrier (SC) signal transmission in a frequency-selective channel. In this paper, we consider SC-HARQ using joint transmit/receive MMSE-FDE and derive a suboptimal set of transmit and receive FDE weights for packet combining. We show by computer simulation that the joint transmit/receive MMSE-FDE offers improved throughput compared to the conventional receive MMSE-FDE.

Recently, we proposed a joint iterative transmit/receive (Tx/Rx) minimum mean square error (MMSE) frequency-domain equalization (FDE) & inter-symbol interference (ISI) cancellation (ISIC) for single-carrier (SC) block transmissions. In this paper, we extend the previously proposed joint iterative Tx/Rx MMSE-FDE & ISIC to the SC hybrid automatic repeat request (HARQ) packet access to exploit the retransmission of the same packet for improving the throughput. We optimize the set of Tx/Rx MMSE-FDE weights by taking into account the packet retransmission/combining as well as ISIC. We show by computer simulation that the proposed scheme significantly improves the packet error rate (PER) and throughput performances in a severe frequency-selective fading channel.

The frequency-domain filtered single-carrier (SC) signal transmission can achieve improved bit error rate (BER) performance due to additional frequency diversity gain while keeping a lower peak-to-average power ratio (PAPR) property than orthogonal frequency division multiplexing (OFDM). In this pa-per, we extend our recently proposed frequency-domain block signal detection (FDBD) with MLD employing QR decomposition and M-algorithm (QRM-MLD) to the frequency-domain filtered SC block transmissions. QR decomposition is applied to a concatenation of the transmit filter, propagation channel, and discrete Fourier transform (DFT). We evaluate BER and throughput performances by computer simulation. From performance evaluation, we discuss how the filter roll-off factor affects the achievable BER and throughput performances and show that as the filter roll-off factor increases, the required number of surviving symbol-candidates in the M-algorithm can be reduced.

Recently, we proposed a frequency-domain block signal detection using maximum likelihood detection (MLD) employing QR decomposition and M-algorithm (QRM-MLD) for the cyclic prefix inserted single-carrier (CP-SC) block transmissions. However, if the number of surviving-symbol candidates is small, the achievable bit error rate (BER) performance degrades, because the probability of removing the correct symbol-candidates at early stages increases. In this paper, to solve this problem, we insert the known training sequence into each data block instead of CP. This SC transmission is called the training sequence-aided SC (TA-SC) block transmissions. We show by computer simulation that the TA-SC can achieve much better BER performance than the CP-SC if the number of surviving symbol-candidates is limited.

Cooperative communications exploit the spatial diversity inherent in multiuser system by allowing cooperation among users having a wide range of channel qualities. How to search the cluster-head and its member relay nodes to cooperate is important. Since nodes are coming into or out of the clusters time to time, the network topology is perturbed and the reconfiguration of the network is unavoidable. In this paper, we propose a new algorithm called stability weighted clustering algorithm (SWCA) to solve this problem. We define the stability by using a new metric of mobility. In the traditional WCA, the speed of every separate node is considered. However, our proposed algorithm introduces a new weight factor, which uses the relative speed of two nodes to represent the mobility of the network. Simulation results show that the SWCA achieves better stability than the traditional WCA while it performs almost the same performance as the WCA with respect to the dominant set update rate and the load balancing factor (LBF).

Multicode direct-sequence code division multiple access (DS-CDMA) can flexibly support multimedia services with various data rates simply by changing the code multiplexing order. The use of simple one-tap frequency-domain equalisation (FDE) at a receiver is known to improve the bit error rate (BER) performance of multicode DS-CDMA in a severe frequency-selective fading environment. However, the BER performance improvement is limited due to the presence of the residual inter-chip interference (ICI). The authors propose a joint transmit/receive minimum mean square error (MMSE) FDE, which carries out one-tap transmit FDE and one-tap receive FDE jointly based on the MMSE criterion. The authors theoretically derive a suboptimal set of transmit and receive FDE weights and investigate the BER performance improvement by computer simulation in a freqeuncy-selective Rayleigh fading channel. The proposed scheme improves the received signal-to-interference plus noise ratio after despreading, and consequently, the BER performance can be significantly improved compared to the conventioal receive MMSE-FDE by (a) making the variations in the equivalent channel gain shallower to reduce the residual ICI for large code multiplexing order U and (b) allocating the transmit power to the frequencies having good condition to improve the received signal-to-noise ratio for a small U. This is conformed by the computer simualtion.

Layered space-time block spread CDMA (LST BSCDMA) has been previously proposed as an alternative to conventional CDMA systems for high-rate mobile communications. This paper proposes two approaches to obtain channel state information (CSI) for LST BS-CDMA system. The basic approach suffers from high computational complexity and poor performance in systems with high order of transmitter diversity due to inter-layer interference (ILI). The second approach reduces computation complexity and eliminates ILI, making it suitable for systems with higher order of transmitter diversity. The detailed simulation studies show that the highly accurate CSI obtained using the improved technique leads to considerable superior performance.

In this letter, we present the performance of broadband bi-directional transmission with analog network coding (ANC) in a frequency-selective fading channel. To cope with the channel frequency-selectivity we introduce the use of frequency domain equalization (FDE) with broadband ANC based on orthogonal frequency division multiplexing (OFDM) and single carrier (SC) radio access. We evaluate, by theory and computer simulation, the achievable bit error rate (BER) and ergodic capacity of bi-directional ANC scheme based on OFDM and SCFDE radio access in a frequency-selective fading channel. Our results show that SC-FDE achieves a better BER performance, but on the other hand, a lower ergodic capacity in comparison with OFDM in a frequency-selective fading channel. Through both analysis and computer simulation, our findings show that a drawback of ANC scheme is its lack of diversity combining at the destination, which causes a slightly lower ergodic capacity in comparison with cooperative relaying irrespective of radio access scheme.

Abstract Direct‐sequence code division multiple access (DS‐CDMA) is a promising uplink access technology for broadband cellular mobile communication systems. In this paper, we propose a joint transmit (Tx)/iterative receive (Rx) frequency‐domain equalization (FDE) for DS‐CDMA. In the proposed scheme, simple one‐tap FDE at the transmitter and iterative one‐tap FDE at the receiver are jointly performed using the common knowledge of channel state information (CSI). Before transmitting the signal, the transmitter predicts the degree of residual inter‐chip interference (ICI) power after the iterations of Rx FDE to determine the Tx FDE weight while the receiver performs the iterative Rx FDE. In practice, it is almost impossible to share the perfect knowledge of CSI. In this paper, a Gaussian approximation of channel estimation (CE) errors is introduced. We theoretically derive a set of Tx and iterative Rx FDE weights based on the minimum mean square error (MMSE) criterion in the presence of the CE error. We show by computer simulation that the proposed scheme provides better bit error rate (BER) performance than the conventional scheme which uses iterative Rx FDE only (i.e., without Tx FDE) even in the presence of CE error. Copyright © 2010 John Wiley & Sons, Ltd.

A simple technique to reduce jitter sensitivity in the bandpass continuous-time delta-sigma modulator is presented. The feedback path in the modulator consists of parallel-connected unit-DACs that are driven by clocks with independent jitters. The outputs of the DACs are summed to form the feedback signal, so that the jitter effects are averaged out. Behavioral simulation shows that the signal-to-noise ratio (SNR) of the proposed modulator is improved by around 10dB by using 10 unit-DACs. It is also shown that the SNR is not sensitive to the mismatch in the unit-DAC output levels.

Cooperative relay diversity and adaptive scheduling for active source/destination pairs in OFDMA-based relay network can significantly improve the reliability of data transmission over wireless fading channels as well as enhance the aggregate and per-link throughputs. However, in slow-varying fading channel, this technique suffers from low per-link throughput since some users with highest SNR at the destination access the channel for a long period while others will have to wait until their channel condition improves. In this paper we propose joint transmit beamforming and fixed cyclic delay diversity (CDD) at the relay nodes to enhance the transmit signals from relays to the destination link and to improve the perlink throughput performance. Combining transmit beamforming with CDD approach creates more fluctuation among subcarriers resulting in time-varying SNR at each destination. Therefore, the scheduler can now successfully provide more chance to users to have access to the channel by allocating subcarriers to users whose SNR are highest and thus the per-link throughput is enhanced. Simulation results show that the system performance using the proposed method increases significantly compared with the other previously proposed cooperative diversity techniques.

Wireless communications are characterized by a multipath propagation that is suitable for application of network coding (NC) to improve the network performance. In particular, a physical layer network coding (PNC) is a promising technique to further improve network capacity for bi-directional information exchange between pairs of end users assisted by a relay terminal. In this paper, we present the performance of bi-directional transmission with PNC in a multipath channel. We introduce the use of frequency domain equalization (FDE) with orthogonal frequency division multiplexing (OFDM) and single carrier (SC) transmission to cope with the channel distortion. The equalization weights based on minimum mean square error (MMSE) criteria required for SC-FDE signaling are derived.

Orthogonal frequency division multiplexing (OFDM) has been adopted for several wireless network standards due to its robustness against multipath fading. Main drawback of OFDM is its high peak-to-average power ratio (PAPR) that causes a signal degradation in a peak-limiting (e.g., clipping) channel leading to a higher bit error rate (BER). At the receiver, the effect of peak-limitation can be removed to some extent to improve the system performance. In this paper, a combined decision-feedback equalization with clipping noise reduction technique is presented. An iterative equalization weight that minimizes the mean square error (MSE) with respect to residual clipping noise is derived. It is shown that the bit error rate (BER) performance of OFDM with proposed technique can be significantly improved in a peak-limited and frequency-selective fading channel.

Radio channel is characterized by a multipath propagation that is suitable for application of network coding (NC) to improve the network capacity. In particular, physical layer network coding (PNC) scheme is known to double the network capacity of bi-directional communication between pairs of end users assisted by a relay terminal in a Gaussian channel. Recently, analog network coding (ANC) has been proposed with a simpler implementation complexity in comparison with PNC scheme, but the same achievable network capacity. On the other hand, an important question is how much the channel capacity is improved over a conventional point-to-point communication in a frequency-selective fading channel. In this paper, we present the ergodic channel capacity analysis of bi-directional transmission with analog network coding in a frequency-selective fading channel. The channel capacity expression for transmission with frequency domain equalization (FDE) is derived based on the Gaussian approximation of the inter-symbol interference (ISI) after FDE.

In the cellular MIMO systems, the system capacity can be increased by multi-user diversity (MUD). On the other hand, the system capacity can also be increased by effective frequency reuse factor allocation (FRF) algorithm. In this paper, a multi-user hybrid FRF algorithm is proposed. Both MUD and effective FRF allocation will be realized. As a result, the system capacity is increased greatly. The system capacities by using the proposed algorithm are theoretically analyzed and the effectiveness of the multi-user hybrid FRF algorithm is testified by numerical results.

In this paper, a frequency domain adaptive antenna array (FD-AAA) algorithm is proposed for the uplink detection in the broadband single-carrier multiple access system. By employing AAA in the frequency domain, the detector is able to suppress both the inter-chip interference (ICI) and the multiuser interference (MUI). Comparison between the proposed FD-AAA algorithm and the frequency domain receive diversity combining (FD-RDC) algorithm is made through simulation. It is shown that when there is no MUI, the bit error rate (BER) performances of the two algorithms are close to each other, i.e., the proposed algorithm can achieve the same frequency diversity gain and receive diversity gain as the FD-RDC algorithm does. However, with the existence of MUI, the proposed algorithm shows a great superiority over the FD-RDC algorithm.

Bit error rate (BER) performance of multicode direct-sequence code division multiple access (DS-CDMA) in a frequency-selective channel severely degrades due to strong inter-chip interference (ICI). Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can take advantage of the channel frequency-selectivity and significantly improve the BER performance. However, the performance improvement is limited by the residual ICI which is present after MMSE-FDE. In this paper, we apply a joint transmit/receive MMSE-FDE (called double MMSE-FDE in this paper) for multicode DS-CDMA signal transmissions to further improve the BER performance. We derive the conditional BER for the given channel realization and evaluate the achievable average BER performance by Monte-Carlo numerical computation method. The BER performance is confirmed by the computer simulation.

In this paper, we study the spectrum selection problem in cognitive radio network with emphasis on resolving the channel contention and the spectrum sharing issues of multiple secondary users. For the traditional channel selection methods, the secondary users select their operating channels based on various criteria. However, these methods neglect the effect that multiple secondary users may content for the same channel if they have the same consensus on one particular good channel. Compared to the existing spectrum selection methods, we consider the sensing-based and the probability-based spectrum selection schemes which can prevent too many secondary users from contending the same channel. An analytical model integrated with the preemptive resume priority M/G/1 queuing network theory is developed to evaluate the overall transmission time of the both schemes. Based on this model, we discuss how to find the optimal selection probability for the probability-based scheme. Furthermore, we also analyze in which condition dependent of sensing time and traffic parameters that the sensing- or the probability-based scheme should be used. Based on the analytical results, we provide a principle to guide system operators which scheme should be used in CR networks. Then, we conclude that channel selection scheme should be adaptive to the variations of the traffic characteristics.

The presence of the multi-access interference (MAI) limits the uplink performance of code division multiple access (CDMA). 2-dimensional (2D) block spread CDMA makes it possible to achieve MAI free uplink transmission while obtaining the frequency diversity gain by using low-complexity single-user frequency-domain equalization (FDE). To further improve the uplink transmission performance, the transmit diversity technique can be used. Cyclic delay transmit diversity (CDTD) can strengthen the frequency-selectivity of the channel. In this paper, we apply CDTD to 2D block spread CDMA with MMSE-FDE. The achievable uplink BER performance is evaluated by computer simulation for both direct sequence CDMA and multi-carrier CDMA. It is shown that CDTD can offer improved uplink BER performance in a frequency-selective uplink channel.

To increase the data rate without signal bandwidth expansion, a combination of MC system with multiple-input multiple-output (MIMO)-space division multiplexing (SDM) is attractive. MIMO-SDM transmission performance is governed by min {Nt, Nr}, where Ntand Nrare the numbers of transmit and receive antennas, respectively. For downlink transmission, many receive antennas cannot be equipped at a mobile station due to space limitation. Therefore, the achievable data rate is limited by the number of receive antennas. In this paper, we propose a virtual MIMO-SDM for multi-carrier-code division multiple access (MC-CDMA) that can use the signals received via different propagation paths as virtual receive antennas. The equivalent number of receive antennas can be increased by a factor of the number of distinct paths of the channel. We confirm, by computer simulation, the effectiveness of virtual MIMO-SDM in a frequency-selective fading channel.

Cooperative networking schemes provide spatial diversity gain (named cooperative diversity gain) using the antennas of spatially distributed users to form a multi antenna transmit situation. A variety of algorithms for orthogonal frequency division multiplexing (OFDM) networks have been developed to achieve cooperative diversity gain. OFDM signals, however, have a problem with a high peak-to-average power ratio (PAPR) leading to lower power efficiency, which may significantly increase the user power consumption. In this paper, instead of conventional OFDM, we present the performance of cooperative network based on OFDM combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency-domain equalization (MMSE-FDE) in a frequency-selective fading channel. To fully exploit the channel frequency-selectivity and achieve a larger frequency diversity gain the equalization weights required for OFDM/TDM signaling based on MMSE criteria are derived.

In the next generation mobile communication systems, high speed data services are expected. However, an unacceptably high transmit power is required. Multi-hop technique can solve this problem. In this paper, we propose a parallel relaying scheme using orthogonal frequency division multiple access (OFDMA), in which the multiple parallel logical routes (one subcarrier is allocated to each link of a logical route) are constructed between a mobile terminal and a base station. Collective construction method, which examines all possible logical routes defined by a physical route and subcarriers to each link along the physical route and selects the best logical route having the maximum channel capacity, requires a prohibitively high complexity. Therefore, we propose a successive construction method. We evaluate the channel capacity of the proposed parallel relaying scheme and compare it with cooperative diversity scheme and also with the conventional single hop network.

Recently, we have proposed an adaptive channel estimation (CE) scheme using one-tap recursive least square (RLS) algorithm (adaptive RLS-CE), where the forgetting factor is adapted to the changing channel condition by the least mean square (LMS) algorithm, for direct sequence-code division multiple access (DS-CDMA) with frequency-domain equalization (FDE). However, the tracking ability for adaptive RLS-CE is limited since the channel estimate obtained from the previously received block is used. In this paper, we introduce the polynomial prediction to improve the tracking ability. We evaluate the bit error rate (BER) performance of DS-CDMA using polynomial prediction RLS-CE in a frequency-selective fast Rayleigh fading channel by computer simulation.

Hybrid automatic repeat request (HARQ) is an indispensable error control technique for wireless packet access. A combination of multi-carrier code division multiple access (MC-CDMA) and HARQ can provide a good throughput performance in a severe frequency-selective fading channel. Recently, we proposed the space-time block coded-joint transmit/receive diversity (STBC-JTRD), which allows an arbitrary number of transmit antennas while limiting the number of receive antennas to 6. In this paper, we evaluate, by computer simulation, the throughput performance of MCCDMA HARQ using STBC-JTRD, and show that the STBCJTRD provides a better throughput performance than the spacetime block coded transmit diversity (STTD).

Abstract-One-tap frequency-domain equalization (FDE) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission in a frequency-selective fading channel. However, a big performance gap from the theoretical lower bound still exists due to the presence of residual intersymbol interference (ISI) after FDE. In this paper, we point out that the frequency-domain received SC signal can be represented similar to the multiple-input multiple-output (MIMO) multiplexing case and then, we propose a new frequency-domain block signal detection, which combines FDE with MIMO signal detection. We apply well-known minimum mean square error (MMSE) detection and Vertical-Bell Laboratories layered spacetime architecture (V-BLAST) detection and evaluate, by computer simulation, the achievable BER performance of SC transmission.

Frequency-domain pre-equalization (pre-FDE) can improve the single-carrier (SC) signal transmission performance in a severe frequency-selective channel. However, the performance improvement is limited by the residual inter-symbol interference (ISI). The residual ISI can be eliminated by the joint use of Tomlinson-Harashima precoding and frequency-domain pre-equalization (called joint THP/pre-FDE) and its performance improvement was confirmed by computer simulation. In this paper, we present a theoretical analysis of joint THP/pre-FDE. The conditional bit error rate (BER) for the given channel realization is derived by taking into account the modulo operation error in a receiver and the achievable BER performance is numerically evaluated.

This paper investigates the effects of channel estimation errors on zero-forcing (ZF) vertical Bell laboratories layered space time (V-BLAST) detection. An analytical method is presented to derive the symbol error probability (SEP) of the signals detected at each stage. The effects of imperfect channel estimation on the SEP performance of V-BLAST detection are then studied. It is shown that ZF-VBLAST detection is very sensitive to the channel estimation errors under high signal to noise ratio (SNR). It is also shown that when optimal ordering is adopted, the effects of channel estimation errors are more significant on the latter detection stages.

In this paper, frequency-domain interleaving on a frame-by-frame basis for orthogonal frequency division multiplexing combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency-domain equalization (MMSE-FDE) is presented. The OFDM/TDM frame signal (i.e., several concatenated OFDM signals) frequency components are interleaved to enhance channel frequency-selectivity and then, MMSE-FDE is applied at the receiver to obtain frequency diversity gain. The bit error rate (BER) performance of OFDM/TDM with and without channel coding is evaluated by computer simulation. It was shown, that frequency-domain interleaving on the frame-by-frame basis for OFDM/TDM using MMSE- FDE achieves a better BER performance in comparison with conventional OFDM due to enhanced frequency diversity gain.

Multicarrier transmission techniques (i.e., orthogonal frequency division multiplexing (OFDM) and multi-carrier code division multiple access (MC-CDMA)) are the promising candidates for wireless access technique in future cellular communication systems because of their capability to eliminate the multipath interference. Multiple-input multiple-output (MIMO)-space division multiplexing (SDM) can increase the transmission rate without bandwidth expansion. A combination of multi-carrier technique and MIMO is a promising technique. However, the transmission performance of MC-CDMA severely degrades because of the inter-code interference (ICI) arising from the orthogonality distortion owing to the frequency- selective fading. In this paper, we derive the channel capacity formula for MC-CDMA MIMO taking into account the ICI and co-channel interference (CCI) in a cellular environment. Many ICI cancellers have been proposed. The cellular channel capacity of MC-CDMA MIMO with perfect ICI cancellation is numerically evaluated and is compared to that of OFDM MIMO in a cellular environment. The impacts of the frequency-reuse factor and the number of propagation paths are also discussed. The numerical computation results show that the cellular channel capacity of MC-CDMA is larger than that of OFDM.

Orthogonal frequency division multiplexing (OFDM) signals have a problem with high peak-to-average power ratio (PAPR). A distortionless selective mapping (SLM) has been proposed to reduce the PAPR, but a high computational complexity prohibits its application to OFDM with a large number of subcarriers. Recently, OFDM combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency-domain equalization (MMSE-FDE) was proposed to improve the transmission performance of conventional OFDM in terms of the bit error rate (BER) and the PAPR. The PAPR problem, however, cannot be completely eliminated. In this paper, we propose a new SLM to further reduce the PAPR of OFDM/TDM. Unlike the conventional OFDM, where SLM is applied over subcarriers in the frequency domain, we propose the new SLM for OFDM/TDM by exploiting both time and frequency dimensions of OFDM/TDM signal. It is shown, by computer simulation that proposed SLM for OFDM/TDM increases the number of candidate sequences in comparison with the conventional SLM, while reducing the PAPR. Furthermore, OFDM/TDM with proposed SLM achieves a lower PAPR than the conventional OFDM with same or reduced computational complexity.

Orthogonal frequency division multiplexing (OFDM) is currently under intense research for broadband wireless transmission due to its robustness against multipath fading. However, OFDM signals have a problem with high peak-to-average power ratio (PAPR) and thus, a power amplifier must be carefully manufactured to have a linear input-output characteristic or to have a large input power backoff. Recently, OFDM combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency domain equalization (MMSE-FDE) was proposed to improve the bit error rate (BER) performance of conventional OFDM while reducing the PAPR. In this paper, by extensive computer simulation, we present a comprehensive performance comparison between OFDM/TDM using MMSE-FDE and conventional OFDM over a frequency-selective fading channel. We discuss about the trade-off among the transmit peak-power efficiency, the spectrum splatter and the BER performance. Our results show that OFDM/TDM using MMSE-FDE achieves almost the same coded BER performance with a several decibels better peak-power efficiency than conventional OFDM, which is significant reduction of amplifier transmit-power backoff, but with a slight decrease in spectrum efficiency.

Single-carrier (SC) transmission using frequency domain equalization (FDE) is one of the candidates for the next generation mobile communication systems expected to deliver high-speed and high-quality packet data services. Fast synchronization is critical for the performance of packet transmission systems. In this paper, a robust timing synchronization scheme for SC-FDE packet transmission is presented and its implementation is discussed. The proposed scheme uses an integration process to find the optimum timing of the guard interval (GI). An SC-FDE packet transmission system is implemented on a FPGA and its performance is analyzed through experimental data.

Recently, we proposed a random transmit power control (TPC) to increase the uplink capacity of DS-CDMA wireless packet access using Rake combining. Furthermore, we evaluated the combined effect of random TPC and inter-path interference (IPI) cancellation and showed that a significant throughput improvement can be achieved if the IPI is sufficiently suppressed. Frequency-domain equalization (FDE) is a promising technique to suppress the IPI. In this paper, we derive an expression for the received signal-to-interference plus noise power ratio (SINR) for a DS-CDMA wireless packet access using FDE and random TPC. Using the derived SINR expression, we evaluate its throughput performance by numerical computation. We compare the throughput using Rake combining with that using FDE to discuss the IPI suppression effect of FDE. It is shown that the throughput using MMSE-FDE approaches that achievable using rake combining w/perfect IC.

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion and frequency-domain inter-chip interference (ICI) cancellation can be incorporated into turbo decoding (this is called the MMSE turbo equalization in this paper) to improve the bit error rate (BER) performance for direct sequence code division multiple access (DS-CDMA). DS-CDMA MMSE turbo equalization requires accurate channel estimation. The performance of MMSE turbo equalization is sensitive to channel estimation accuracy. Recently, we proposed a 2-step maximum likelihood channel estimation (MLCE) for DS-CDMA with FDE. In this paper, we apply 2-step MLCE to DS-CDMA MMSE turbo equalization and evaluate by computer simulation the achievable BER performance in a frequency-selective block Rayleigh fading channel.

In mobile communication systems, high speed packet data services are demanded. In the high speed data transmission, throughput degrades severely due to severe inter-path interference (IPI). Recently, we proposed a random transmit power control (TPC) to increase the up link throughput of DS- CDMA packet mobile communications. In this paper, we apply IPI cancellation in addition to the random TPC. We derive the numerical expression of the received signal-to-interference plus noise power ratio (SINR) and introduce IPI cancellation factor. Then we evaluate, by Monte-Carlo numerical computation method, the combined effect of random TPC and IPI cancellation on the uplink throughput of DS-CDMA packet mobile communications.

This paper addresses the problem of performance analysis for maximum likelihood (ML) detection in two-input multiple-output multiplexing systems. A novel analytical method is presented to formulate the symbol error probability (SEP). Based on the total probability theory, the SEPs of the two transmitted signals are obtained in closed-form by solving the SEP equations. Both equal and unequal power allocations are investigated. The accuracy of the proposed method is verified by Monte-Carlo simulations. The proposed method can also be extended to systems with more than two inputs.

In this paper, an analytical approach to performance analysis of vertical Bell laboratories layered space time (V-BLAST) detection with optimal ordering for systems with two transmit antennas is presented. The post-detection signal-to-noise-ratio (SNR) at each stage is derived and the symbol error probabilities (SEP) of the signals are then given in closed-form. The analysis takes into account the effects of optimal ordering, imperfect channel estimation and error propagation, which were rarely considered in the literature due to the difficulties in evaluation. The accuracy of the analysis is demonstrated by Monte-Carlo simulations.

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can provide a better bit error rate (BER) performance than rake combining. However, the residual inter-chip interference (ICI) is produced after MMSE-FDE and degrades the BER performance. Recently, we showed that frequency-domain ICI cancellation can bring the BER performance close to the theoretical lower bound. To further improve the BER performance, transmit antenna diversity technique is effective. Cyclic delay transmit diversity (CDTD) can increase the number of equivalent paths and hence achieve a large frequency diversity gain. Space-time transmit diversity (STTD) can obtain antenna diversity gain due to the space-time coding and achieve a better BER performance than CDTD. In this paper, we point out that the performance difference between CDTD and STTD is mainly due to the residual ICI. We theoretically show that the introduction of ICI cancellation into DS-CDMA/MMSE-FDE gives almost the same BER performance for CDTD and STTD. This is confirmed by computer simulation.

Recently, frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion has been attracting much attention to overcome the frequency-selective fading channel. The bit error rate (BER) performance of single- carrier (SC) transmission is significantly improved by using MMSE-FDE by obtaining the frequency-diversity gain while suppressing the inter-symbol interference (ISI). However, the residual ISI after MMSE-FDE limits the performance improvement. Recently, we have proposed a joint use of Tomlinson-Harashima precoding (THP) and FDE reception (joint THP/FDE) to suppress the residual ISI. However, joint THP/FDE requires the channel state information (CSI) at both the transmitter and receiver. In this paper, we replace FDE reception by pre-FDE and propose joint THP/pre-FDE that requires the CSI at the transmitter only, while providing almost the same BER performance as joint THP/FDE.

In multicarrier code division multiple access (MC-CDMA), a good bit error rate (BER) performance can be achieved by using frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion. However, the presence of residual inter-code interference (ICI) after MMSE-FDE and despreading degrades the BER performance of the multi-code MC-CDMA. The use of ICI cancellation can improve the BER performance of the multi-code MC-CDMA. To further improve the BER performance, transmit diversity technique is effective. In this paper, cyclic delay transmit diversity (CDTD) is considered. CDTD can achieve the frequency diversity gain, whereas the well-known space-time transmit diversity (STTD) can achieve the antenna diversity gain owing to the space-time coding and provide a better BER performance than CDTD. It is shown in this paper that the performance degradation of CDTD is mainly due to the residual ICI after MMSE-FDE. In order to achieve a good BER performance, the multi-code MC-CDMA using joint CDTD and ICI cancellation is proposed, and its BER performance is evaluated by computer simulation.

The uplink (mobile-to-base) bit error rate (BER) performance is significantly degraded due to the multi-access interference (MAI). Recently, we have proposed a new hybrid multi-access technique, called delay-time/code division multiaccess (DT/CDMA). A different user is assigned a different cyclic time delay and/or spreading code. DT/CDMA can obtain the frequency diversity gain while suppressing the MAI. In the previous paper, time-domain spreading was considered. In this paper, we consider frequency-domain spreading and compare the achievable BER performances of DT/CDMA using time-domain spreading and frequency-domain spreading.

Antenna diversity is an effective technique for improving the transmission performance in a multi-path fading channel. Recently, we proposed the space-time block coded-joint transmit/receive antenna diversity (STBC-JTRD), which allows the use of an arbitrary number of transmit antennas without sacrificing the coding rate. However, in STBC-JTRD, the number of receive antennas is limited to 4. In this paper, we show the STBC-JTRD encoding allowing the use of more than 5 receive antennas. The bit error rate (BER) analysis in a frequency-nonselective Rayleigh fading channel is presented. The BER performance analysis is confirmed by computer simulation.

To increase the transmission rate without bandwidth expansion, multiple-input multiple-output (MIMO) technique has been attracting much attention. When MIMO technique is applied to a cellular system, the MIMO channel capacity is affected by the interference from neighboring co-channel cells. In this paper, we evaluate the outage probability of MIMO downlink channel capacity in a cellular system, taking into account the frequency-reuse factor, path loss exponent, standard deviation of shadowing loss, and base station (BS) transmit power. We discuss about the cellular channel capacity. Furthermore, we compare the cellular MIMO channel capacity with those of other multi-antenna transmission techniques such as space time block coded multiple-input single-output (STBC-MISO) and single-input multiple-output (SIMO). We show that the optimum frequency reuse factor is 3 irrespective of type of multi-antenna transmission scheme for the outage probability of 10 %. We also show that the cellular MIMO channel capacity is always higher than those of SIMO and MISO.

Broadband packet data services are demanded in the next generation mobile communications systems. Multi-carrier CDMA (MC-CDMA) is considered to be a promising wireless technique. Hybrid ARQ (HARQ) is a powerful error control technique. It is known that the HARQ throughput performance of MC-CDMA degrades due to the residual inter-code interference (ICI) after frequency-domain equalization (FDE). The use of frequency-domain soft interference cancellation FDSIQ technique can reduce the residual ICI and improve the throughput performance. An important technical problem is the generation of accurate residual ICI replica for FDSIC. In this paper, we consider low-density parity-check coded (LDPC- coded) MC-CDMA HARQ and generate the residual ICI replica from a-posteriori log-likelihood ratio (LLR) obtained by the LDPC decoder. We evaluate, by computer simulation, the throughput performance in a frequency-selective Rayleigh fading channel. We show that if the residual ICI is removed MC- CDMA can provide better throughput performance than orthogonal frequency division multiplexing (OFDM).

The bit error rate (BER) performance of single-carrier (SC) transmission in a frequency-selective fading channel can be significantly improved by using frequency-domain equalization (FDE). In a cellular network, however, the same frequency is reused in different cells to efficiently utilize the limited bandwidth and therefore, the BER performance degrades due to co-channel interference (CCI). Adaptive antenna array (AAA) is one of the well-known techniques to suppress the CCI. In this paper, we consider a frequency-domain AAA, based on the average CCI power minimization criterion, jointly used with FDE and theoretically derive the optimum array weight using Lagrange multiplier method. We evaluate, by the computer simulation, the outage probability of the BER in a frequency-selective CCI environment.

2-dimensional (2D) block spread direct sequence-code division multiple access (DS-CDMA) allows uplink mutli- rate/mutli-connection transmissions without causing a serious multi-access interference (MAI) in the presence of a frequency- selective fading channel. However, in a cellular system, the inter- cell interference remains. The site selection diversity (SSD) can be used to reduce the inter-cell interference and increase the uplink capacity. Furthermore, transmit power control (TPC) is necessary to combat the near-far problem. In this paper, we discuss the impact of SSD and TPC on the uplink capacity of 2D block spread DS-CDMA and compare it with those of conventional DS-CDMA and ID block spread DS-CDMA.

A single-carrier frequency-interleaved spread spectrum multiple access (SC-FI-SSMA), which we recently proposed, uses frequency-domain interleaving and MMSE-FDE to remove the uplink multi-user interference (MUI) while achieving the frequency diversity gain by assigning the orthogonal interleaving matrices to different users. However, in a multi-cell environment, the uplink capacity of SC-FI-SSMA may degrade due to the inter-cell interference. To improve the uplink bit error rate (BER) performance, transmit power control and site selection diversity techniques can be applied. In this paper, we evaluate the uplink capacity of SC-FI-SSMA to show that SC-FI-SSMA provides better uplink performance than DS-CDMA even in a multi-cell environment.

Hybrid automatic repeat request (HARQ) is an indispensable technique for packet access. This is employed in high speed downlink packet access (HSDPA) using the orthogonal multicode direct sequence code division multiple access (DS-CDMA). As the data rate increases, the frequency-selectivity of the channel becomes severer and some equalization technique other than rake combining is necessary. The use of MMSE frequency-domain equalization (MMSE-FDE) can significantly improve the throughput performance. However, the residual inter-chip-inference (ICI) after MMSE-FDE produces the orthogonality distortion among the spreading codes and the throughput performance is far from the theoretical lower bound. In this paper, we study an MMSE turbo equalization for HARQ using multicode DS-CDMA. It is shown by computer simulation that MMSE turbo equalization can significantly improve the throughput performance. An ES/N0reduction of as much as 2.5-3 dB from the no turbo equalization case is obtained for a throughput range of 2-2.5 bit/s/Hz.

In the next generation mobile communication systems, high-speed and high-quality packet data services are demanded. Hybrid ARQ (HARQ) is known as one of the promising error control techniques for wireless packet transmission. However, in a severe frequency-selective fading channel, the single-carrier (SC) HARQ throughput performance degrades due to inter-next generation mobile communication hybrid ARQ intersymbol interference Tomlinson-Harashima precoding frequency-domain equalization frequency-diversity gain Rayleigh fading channelsymbol interference (ISI). In this paper, we consider joint Tomlinson-Harashima precoding (THP) and frequency-domain equalization (FDE) to obtain the frequency-diversity gain while suppressing the residual ISI after FDE. We evaluate, by computer simulation, the SC HARQ throughput performance using joint THP/FDE in a frequency-selective Rayleigh fading channel.

Recently, multi-carrier code division multiple access (MC-CDMA) has been attracting much attention for the next generation mobile communications systems. Using frequency-domain equalization based on minimum mean square error criterion (MMSE-FDE), the frequency diversity effect can be obtained and improved bit error rate (BER) performance can be obtained. Antenna diversity is an effective technique to further improve the BER performance. Space-time transmit diversity (STTD) is suitable for the downlink transmission. Recently, overlap FDE that requires no guard interval (GI) insertion are presented. Combining STTD decoding and overlap FDE is not straightforward. In this paper, we propose STTD decoding for the MC-CDMA transmission using overlap FDE and then, its BER performance is evaluated by computer simulation.

We present, in this paper, pilot-assisted channel estimation (CE) for orthogonal frequency division multiplexing combined with time division multiplexing (OFDM/TDM) using minimum mean square error frequency-domain equalization (MMSE-FDE) over a nonlinear and frequency-selective fading channel. Joint use of time-domain filtering to increase the signal-to-noise ratio (SNR) of pilot signal and frequency-domain interpolation for OFDM/TDM is presented. The simulation results show that OFDM/TDM with proposed pilot-assisted CE provides a better performance than OFDM since the peak-to-average power ratio (PAPR) problem can be reduced.

2D block spread direct sequence-code division multiple access (DS-CDMA) allows multi-rate/multi-connection without causing downlink multi-access interference (MAI) in the presence of a frequency-selective fading channel. However, in a cellular system, the inter-cell interference remains. The site selection diversity transmission (SSDT) can be used to reduce the inter-cell interference and increase the downlink capacity. In this paper, we show that if adaptive power allocation is applied, where the BS allocates different power levels to different users according to their channel conditions, 2D block spread DS-CDMA with SSDT provides larger downlink capacity than the conventional DS-CDMA with SSDT.

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can significantly improve the downlink bit error rate (BER) performance of DS-CDMA in a frequency-selective fading channel. However, the uplink BER performance degrades due to a strong multi-user interference (MUI). We have proposed frequency-interleaved single-carrier spread spectrum multi-access (SC-SSMA) with MMSE-FDE, in which the subcarrier components of each user's signal are interleaved onto a wider bandwidth. Since frequency-interleaving patterns assigned to different users are orthogonal to each other, frequency-interleaved SC-SSMA can avoid the MUI completely while achieving frequency diversity gain with MMSE-FDE. In this paper, transmit/receive antenna diversity is applied to frequency-interleaved SC-SSMA with MMSE-FDE to further improve the BER performance. Its conditional BER is derived for the given set of channel gains. The average BER performance is numerically evaluated using the derived conditional BER and is confirmed by computer simulation.

The single-carrier (SC) transmission performance degrades due to inter-symbol interference (ISI) in a frequency-selective fading channel. To improve the transmission performance, joint use of Tomlinson-Harashima precoding (THP) and frequency-domain equalization (FDE) is promising. In this paper, we derive the conditional bit error rate (BER) for the given set of channel gains in a frequency-selective Rayleigh fading channel. We evaluate the average BER performance by Monte-Carlo numerical computation method using the derived conditional BER. The theoretical analysis is confirmed by computer simulation of the signal transmission.

MC DS-CDMA is a combination of OFDM and time-domain spreading, while MC-CDMA is a combination of OFDM and frequency-domain spreading. In MC-CDMA, a good bit error rate (BER) performance can be achieved by using frequency-domain equalization (FDE), since the frequency diversity gain is obtained. On the other hand, the conventional MC DS-CDMA cannot obtain the frequency diversity gain. In this paper, the authors propose MC DS-CDMA that can obtain the frequency diversity gain by applying FDE. The conditional BER analysis is presented. The theoretical average BER performance in a frequency-selective Rayleigh fading channel is evaluated by Monte-Carlo numerical computation method using the derived conditional BER and is confirmed by computer simulation of the MC DS-CDMA signal transmission.

Abstract The most important technical challenge for the realization of 4G mobile networks is twofold: (a) to overcome the highly frequency‐selective fading channel and (b) to significantly reduce the transmit power from mobile terminals. Recently, it has been shown that the application of frequency‐domain equalization (FDE) can take advantage of channel frequency‐selectivity and improve the transmission performance of single‐carrier (SC) as well as multi‐carrier (MC) signal transmissions. Either SC or MC can be used for the downlink (base‐to‐mobile) to achieve almost the same bit error rate (BER) performance. However, for the uplink (mobile‐to‐base) applications, SC transmission is more appropriate since it has less peak power. For broadband data transmissions, transmit power reduction is a very important issue. Applying wireless multi‐hop technique is a possible solution to this issue. In this paper, we will discuss about some important 4G wireless techniques. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract R&D on new generation mobile network has attracted a growing interest over the world on the background of rapid market growth for 2nd and 3rd generation cellular networks and wireless LANs/MANs. The National Institute of Information and Communications Technology (NICT) started the New Generation Mobile Network Project in April 2002, and has developed fundamental technologies to enable seamless and secure integration of various wireless access networks such as existing cellular networks, wireless LANs, home networks, intelligent transport systems (ITS), the Beyond‐3G (B3G) cellular and other wireless access systems. This paper overviews the achievements of the project focusing on network and access technologies. Copyright © 2007 John Wiley & Sons, Ltd.

A multi-hop virtual cellular network (VCN) was proposed for future mobile communication systems. In VCN, the transmitted signal from a mobile terminal is relayed via multi-hop links to the central port, which is the gateway to the core network. In the original multi-hop VCN, a call is blocked when there is no channel available at one link over the multi-hop route. However, the use of a sub- route when a link failure occurs can be a solution to avoid the blocking of this call. In this paper, we propose a relay skipping method to avoid the call blocking in a DS-CDMA VCN. Computer simulation is conducted to evaluate the impact of the proposed method on the blocking probability of the multi-hop VCN and make comparison with the present cellular network as well.

In order to avoid the large peak transmit power, resulting from the high transmission rates expected for future mobile communication systems, a wireless multi-hop virtual cellular network (VCN) was recently proposed. In VCN, the transmitted signal from a mobile terminal is relayed via multi-hop links to the central port, which is the gateway to the core network. With the use of a routing algorithm based on the total uplink transmit power minimization criterion, the total transmit power of all the multi-hop links between the mobile terminal and the central port can be significantly reduced, in comparison with the present (single-hop) cellular network. Reducing the transmit power per communication contributes to reducing the interference power and hence the system capacity may be enlarged. In this paper, an "on-demand" channel assignment strategy, using the channel segregation dynamic channel allocation (CS-DCA) algorithm, is proposed for multi-hop DS-CDMA VCN. Computer simulation is conducted to evaluate the blocking probability performance and make a comparison between the VCN and the present cellular network

The OFDM signals have a problem of high peak-to-average power ratio (PAPR). Hence, a large transmit-power backoff or amplitude clipping is required. The amplitude clipping causes signal degradation and the BER performance increases. A trade-off between the PAPR reduction and the BER performance is present; the PAPR reduces as the level of clipping reduces, but the BER degrades due to signal distortion. Recently, we proposed OFDM combined with time division multiplexing (OFDM/TDM) to alleviate the high PAPR problem, while achieving better BER performance than OFDM. In this paper, a theoretical bit error rate (BER) analysis of clipped OFDM/TDM system in a frequency-selective fading channel is developed. The average BER performance is evaluated by numerical computation using the derived conditional BER and by computer simulation. It is shown that OFDM/TDM can significantly reduce the amplitude clipping level and the required average signal energy per bit-to-AWGN power spectrum density ratio Eb/Nofor the given BER in comparison to conventional OFDM.

Frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion can significantly improve the BER performance of DS- and MC-CDMA signal transmissions in a severe frequency-selective fading channel. However, since the frequency-distorted signal cannot be completely equalized, the residual inter-code interference (ICI) limits the BER performance improvement. In 4G systems, much higher variable rate data services than in the present 3G systems are required. Orthogonal multicode transmission technique has flexibility in offering variable rate services. However, the BER performance degrades as the number of parallel codes increases. In this paper, we propose a frequency-domain soft interference cancellation (FDSIC) for multicode DS- and MC-CDMA signal transmissions and their achievable BER performances are evaluated by computer simulation

The multiple-access interference (MAI) limits the performance of the DS-CDMA uplink transmission. 2 dimensional (2D) spread/chip-interleaved DS-CDMA is an MAI-free system, where single-user coherent frequency- domain equalization (FDE) can be used instead of complicated multiuser detection (MUD). However, coherent FDE needs channel estimation. Pilot-assisted channel estimation is not reliable in a fast fading environment. In this paper, we apply joint frequency- domain differential detection and equalization (FDDDE) that requires no channel estimation to 2D spread/chip- interleaved DS-CDMA in a multiuser/multipath environment. The filter coefficient used in FDDDE is updated by estimating the normalized Doppler frequency. Computer simulation results show that 2D spread/chip- interleaved DS-CDMA using FDDDE is robust against fast fading.

Chip interleaving technique has been proposed for DS-CDMA to eliminate the multiple-access interference (MAI). In this paper, we develop this technique to provide the single- or multicarrier CDMA with flexible low-to-high bit rate transmission by jointly using 2-dimensional (2D) OVSF spreading and chip interleaving for quasi-synchronous uplink transmissions in time- and frequency-selective fading channels. Through appropriate design of 2D spreading code assignment, not only the maximum time- and frequency-domain diversity can be achieved but also users are equipped with multi-rate services. The complexity of receivers is greatly reduced since single-user frequency-domain equalization (FDE) based on the MMSE criterion can be applied for signal detection. Computer simulation results show that the multi-rate transmission is possible for the 2D OVSF spread/chip-interleaved CDMA uplink and the bit error rate (BER) performance with turbo coding is very robust against Doppler spread

Broadband wireless packet access will be the core technology of the next generation mobile communication systems. For very high-speed and high-quality packet transmissions in a limited bandwidth, the joint use of multiple-input multiple-output (MIMO) multiplexing and hybrid ARQ (HARQ) is an effective method. However, if single-carrier (SC) transmission is used, the transmission performance significantly degrades due to a large inter-symbol interference (ISI) resulting from a severe frequency-selective fading. In this paper, we propose an iterative frequency-domain successive interference cancellation (SIC) with two dimensional (2D) MMSE-FDE. At each iteration stage, the successive signal detection/cancellation is performed according to the descending order of the signal reliability. However, since the interference from the other transmit antennas can be only partially cancelled by performing SIC, the residual interference is present at the output of SIC. In this paper, we propose to update the 2D MMSE-FDE weights at each signal detection in order to suppress simultaneously the ISI and the interference from other antennas while obtaining antenna and frequency diversity gain. However, since a single use of SIC with 2D MMSE-FDE is insufficient, it is repeated a sufficient number of times. The bit error rate (BER) and HARQ throughput performance in a frequency-selective Rayleigh fading channel are evaluated by computer simulation.

Broadband wireless packet access will be the core technology of the next generation mobile communication systems. For very high-speed and high-quality packet transmissions, the joint use of multiple-input multiple-output (MIMO) multiplexing and hybrid ARQ (HARQ) is very effective. However, if single-carrier (SC) transmission is used, the transmission performance significantly degrades due to a large inter-symbol interference (ISI) resulting from a severe frequency-selective fading. Recently, we proposed a frequency-domain iterative parallel interference cancellation (PIC) for SC-MIMO multiplexing. For signal separation, 2 dimensional minimum mean square error (2D MMSE)-FDE is performed at first. Then, the joint PIC and ID MMSE-FDE is repeated a sufficient number of times. However, the interference from other transmit antennas still remains at the outputs of PIC. Therefore, in this paper, we propose to use 2D MMSE-FDE instead of ID MMSE-FDE in each iteration and investigate, by computer simulation, the achievable bit error rate (BER) and throughput performance of HARQ in a frequency-selective Rayleigh fading channel

In wireless communications, the channel consists of many resolvable paths with different time delays, resulting in a severely frequency-selective fading channel. The frequency-domain equalization (FDE) can take advantage of the channel selectivity and improve the bit error rate (BER) performance of the single-carrier (SC) transmission. Recently, multi-input multi-output (MIMO) multiplexing is gaining much attention for achieving very high speed data transmissions under limited bandwidth. Eigenbeam space division multiplexing (E-SDM) is known as one of MIMO multiplexing techniques. In this paper, we propose frequency-domain E-SDM for SC transmission. In frequency-domain E-SDM, the orthogonal transmission channels to transmit different data in parallel are constructed at each orthogonal frequency. At a receiver, FDE is used to suppress the ISI. In this paper, for high spectrum efficiency, the transmit power allocation and the adaptive modulation based on the equivalent channel gains after performing FDE are applied. The transmission performance of the frequency-domain E-SDM in a severe frequency-selective Rayleigh fading channel is evaluated by computer simulation.

This paper presents a hybrid automatic repeat request (HARQ) with variable spreading factor (VSF) suitable for a multicarrier code division multiple access (MC-CDMA). We consider a HARQ based on incremental redundancy (IR) strategy. The throughput of MC-CDMA HARQ is a tradeoff among the frequency diversity gain, the coding gain and the inter-code interference (ICI). In order to effectively exploit the channel frequency-selectivity and the channel coding, the spreading factor is changed between the initial transmission and the succeeding retransmissions. The throughput performance of HARQ with VSF in a frequency-selective Rayleigh fading channel is evaluated by the computer simulation and compared with that with fixed spreading factor (FSF). It is shown that HARQ with VSF can provide better throughput performance than with FSF and is particularly useful when high-level modulation (e.g., 16QAM and 64QAM) is used. The impacts of fading correlation between packet retransmissions and the channel frequency-selectivity on achievable throughput performance are discussed

The bit error rate (BER) performance of downlink DS-CDMA in a frequency-selective fading channel can be significantly improved by the use of frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion. However, the presence of residual inter-chip-inference (ICI) after FDE produces the orthogonality distortion among the spreading codes and the BER performance degrades as the number of multiplex order increases. In this paper, we propose a joint MMSE-FDE and ICI cancellation to improve the BER performance of the DS-CDMA downlink. In the proposed scheme, the residual ICI replica in the frequency-domain is generated and subtracted from each frequency component of the received signal after MMSE-FDE. The MMSE weight at each iteration is derived taking into account the residual ICI. The effect of the proposed ICI cancellation scheme is confirmed by computer simulation

Frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion can replace the conventional rake combining with significantly improved bit error rate (BER) performance for the downlink DS-CDMA in a frequency-selective fading channel. Recently, a new MMSE-FDE technique that requires no GI insertion has been proposed to avoid inter-block interference (IBI) (this technique is called overlap FDE). However, the residual IBI is produced and degrades the BER performance. Furthermore, the presence of an inter-chip interference (ICI) after MMSE-FDE limits the BER performance improvement. In this paper, we propose an iterative overlap FDE for DS-CDMA downlink to suppress both IBI and ICI. In the iterative overlap FDE, joint MMSE-FDE and ICI cancellation is repeated a sufficient number of times and the middle part of M chips is picked up. The BER performance with the iterative overlap FDE is evaluated by computer simulation.

The next-generation mobile communications system is anticipated to support very high-speed data rates exceeding several tens megabits per second. In this paper, we consider high-speed downlink packet access for direct-sequence code-division multiple access (DS-CDMA) as in third-generation wideband code-division multiple-access systems. Adaptive modulation and coding (AMC), multicode operation and hybrid automatic repeat request (HARQ) will be the enabling technologies. With such high-speed data transmissions, however, multicode operation severely suffers from the loss of orthogonality among the spreading codes since the wireless channel becomes severely frequency-selective. In this paper, we apply frequency-domain equalization (FDE) based on minimum mean-square error (MMSE) criterion instead of conventional rake combining for receiving the packet. A new MMSE-FDE weight is derived for packet combining. The throughput in a frequency-selective Rayleigh-fading channel is evaluated by computer simulation for Chase combining and incremental redundancy (IR) packet combining. It is shown that the use of MMSE-FDE for the reception of multicode DS-CDMA packet gives an improved throughput irrespective of the channel's frequency-selectivity.

It has been revealed that direct sequence code-division multiple access (DS-CDMA) can achieve a good bit-error rate (BER) performance, comparable to multicarrier CDMA (MC-CDMA), by using coherent frequency-domain equalization (FDE) instead of coherent Rake combining. However, coherent FDE requires accurate channel estimation. Pilot-assisted channel estimation is a practical solution, but its accuracy is sensitive to the Doppler spread. In this paper, a frequency-domain differential encoding and detection scheme is proposed for a DS-CDMA mobile radio. Joint frequency-domain differential detection and equalization (FDDDE) based on minimum mean-square error (MMSE) criterion is presented, where a simple decision feedback filter is used to provide a reliable reference signal for MMSE-FDDDE. Also presented is an approximate BER analysis. It is confirmed by both approximate BER analysis and computer simulation that MMSE-FDDDE provides good BER performance close to the coherent MMSE-FDE and shows high robustness against the Doppler spread; it outperforms coherent MMSE-FDE for large Doppler spreads. The proposed MMSE-FDDDE can also be applied to MC-CDMA. A performance comparison between uncoded DS- and MC-CDMA shows that DS-CDMA with MMSE-FDDDE achieves better BER performance than MC-CDMA with MMSE-FDDDE for small spreading factors.

Abstract In this paper, we present a comprehensive performance evaluation of chip interleaving effect on turbo coded direct sequence spread spectrum (DS‐SS) system in a frequency non‐selective Rayleigh fading channel with antenna diversity reception. At the transmitter, chip interleaver scrambles the SF (spreading factor) chips associated with a data symbol and transforms the transmission channel into a highly time‐selective or highly memoryless channel at the chip level. The use of chip interleaving is equivalent to using SF‐antenna diversity reception with correlated fading among the branches and with reduced average received signal power per antenna by a factor of SF. We theoretically analyze how chip interleaving alters the received signal statistics. Then, the effect of the various parameters, viz. interleaver size, interleaving depth, information sequence length, spreading factor and the fading maximum Doppler frequency, are also evaluated. It is found that the bit error rate (BER) performance improves with increasing spreading factor and increasing frame length. Chip interleaving is found to be effective in the presence of receive antenna diversity as well. Copyright © 2005 John Wiley & Sons, Ltd.

The 3G cellular system has infiltrated into the market and the next generation wireless system called beyond 3G is discussed at ITU-R. The beyond 3G system integrates various wireless accesses, including 3G and wireless LANs, and provides an all IP wireless solution to services that take advantage of each wireless communication of the system. Current approach to integrate wireless systems localizes wireless dependent functions and integrates all IP network using IP technologies. We propose a scalable mobile Ethernet architecture for the all IP integrated network using MAC layer technologies, such as provider bridge, RPR, and IEEE 802, and the fast vertical handover introducing common radio resource and signaling managements. We discuss network segmentation with mobility management and multicast management for the scalability of the mobile Ethernet by reducing network traffic. We evaluate the network from the viewpoint of scalability. In the evaluation, we understand that the design of the gateway switch of a segment forwarding MAC frames as an anchor point becomes effective in cases where the gateway switch of each segment cannot hold entries for all mobile terminals. We also evaluate the vertical handover as compared to the mobile IPv6 fast handover, and we understand that the fast vertical handover consumes less network resources and is flexible in having an anchor point for handover.

A closed-form formula for symbol-error rate (SER) of an orthogonal frequency-division multiplexing (OFDM) system with M-ary differential phase-shift keying (MDPSK) in frequency domain over Rayleigh fading channels is obtained. It is found that, by MDPSK in frequency domain, identical SERs can be achieved on all subcarriers. However, both time and frequency dispersion in the channel will introduce error floors. A comparison between OFDM-MDPSK in frequency domain and that in time domain reveals that the former system offers superior SER performance in a fast fading environment, while the latter performs better if the channel is mainly frequency selective. Moreover, the former system has lower implementation complexity.

A three-stage coherent multistage interference canceller (COMSIC) employing pilot symbol-assisted (PSA) channel estimation for replica generation of multiple access interference (MAI) is implemented and its performance in the presence of frequency selective multipath fading is experimentally evaluated by a multipath fading simulator. A fast transmission power control (TPC) method suitable for COMSIC is also proposed, in which the signal-to-interference plus background noise power ratio (SIR) at the matched filter (MF) based RAKE receiver is measured to achieve a short TPC delay and the target signal-to-interference ratio value is compensated by an outer loop so that the measured block error rate (BLER) is equal to the prescribed target value. The experimental results show that as expected the COMSIC satisfactorily reduces the MAI even when the number of active users is equal to the spreading factor in a multipath fading environment, and thus, improves the bit error rate (BER) performance in a multiuser environment. The results also show that the proposed fast TPC method with a two-slot delay associated with COMSIC works satisfactorily and the combination of COMSIC and fast TPC significantly decreases the transmission power of a mobile station (required transmission power of a mobile station with COMSIC at the average BER of 10/sup -3/ is decreased by approximately 2.0 (3.0) dB compared with the MF-based RAKE receiver with (without) antenna diversity reception). This extends the cell coverage, battery life, and increases the system capacity in the reverse link.

The combined effect of coherent RAKE combining using the weighted multislot averaging (WMSA) channel estimation filter and closed-loop fast transmit power control (TPC) in the 4.096 Mchip/s direct sequence code division multiple access (DS-CDMA) mobile radio reverse link is experimentally evaluated. The WMSA channel estimation filter utilizes periodically transmitted pilot symbols (four pilot symbols are time-multiplexed in each 40-symbol time slot). Its observation period is extended to 2-K slots in order to improve the accuracy of the channel estimation. The fast TPC is based on the measurement of signal-to-interference plus background noise ratio (SIR) using pilot symbols. Laboratory experiments show that the use of the K=2 WMSA channel estimation filter reduces the required E/sub b//I/sub 0/ at the average BER of 10/sup -3/ by approximately 0.5 dB compared to use of the linear interpolation filter, and that the required E/sub b//I/sub 0/ is minimized when the SIR measurement interval is M=10 symbols (one slot TPC delay). It was also clarified that SIR-based TPC works satisfactorily when two users with different information data rates, i.e., SF, independently employ fast TPC. Field experimental results obtained in an area nearby Tokyo showed that the average BER of 10/sup -3/ is achieved at the target E/sub b//I/sub 0/ per antenna of approximately 2.5 dB by using four-finger branch RAKE and two-branch antenna diversity. Although the target E/sub b//I/sub 0/ to achieve same BER, when there is one interfering user with a fourfold greater transmit power than that of the desired user that independently employs fast TPC, is almost the same as that in the single-user case, the mobile transmit power is increased by 1.0-2.0 dB due to the increased MAI. These results indicate that the combination of coherent RAKE combining and fast TPC works well in practical multipath fading channels.

In wideband direct sequence code division multiple access (W-CDMA), employing an adaptive antenna array is a very promising technique to reduce severe multiple access interference (MAI) from high rate users. A four-antenna pilot symbol-assisted coherent adaptive antenna array diversity (PSA-CAAAD) receiver comprising an adaptive antenna array based on a minimum mean squared error (MMSE) criterion and a RAKE combiner is implemented in preliminary laboratory and field experiments. There are two important design concepts of the PSA-CAAAD receiver. The first is that the adaptive antenna array forms an antenna beam for each resolved propagation path and tracks only slow changes in the directions of arrival (DOAs) and average powers of the desired and interfering user signals. The second is that the RAKE combiner tracks the instantaneous changes in channel conditions and coherently combines the signals of the desired user propagating along the resolved paths to maximize the instantaneous signal-to-interference plus background noise power ratio (SINR). This paper presents, both by laboratory and field experiments, the effectiveness of PSA-CAAAD receiver as a powerful means to reduce severe MAI from high rate users, and that it is more effective than using a space diversity receiver with the same number of antennas in the W-CDMA reverse link.

A 3-stage coherent multistage interference canceller for DS-CDMA mobile radio was implemented and its performance in a frequency selective multipath fading channel is experimentally evaluated by using a multipath fading simulator. The implemented interference canceller applied pilot symbol-assisted channel estimation for data decision and replica generation of multiple access interference (MAI). The laboratory experiment demonstrated that, as is expected, the coherent multistage interference canceller can reduce the MAI to satisfactory levels in a multipath fading environment and thus, improving the bit error rate (BER) performance under multiuser environment.

Coherent DS-CDMA forward and reverse links periodically transmitting pilot symbols every data slot to estimate the fading channels are considered; Np-pilot systems are placed at the beginning of each data slot. A pilot symbol-assisted channel estimation scheme that uses weighted multi-slot averaging (WMSA) is presented for coherent RAKE combining. The BER performance achievable by WMSA coherent RAKE combining is evaluated by computer simulations under multipath Rayleigh fading environments and compared with those of other channel estimation methods. For the DS-CDMA reverse link, fast transmit power control (TPC) based on measured signal-to-interference plus noise ratio (SINR) is employed so the simulation also considers fast closed loop TPC. It is demonstrated by computer simulations that the required signal energy per bit-to-background noise power spectrum density ratio (E/sub b//N/sub 0/) can be reduced by about 0.8 dB compared to RAKE combining using simple linear interpolation and that the E/sub b//N/sub 0/ loss from the ideal channel estimation is as small as 0.5 dB both with and without antenna diversity. The BER performance achievable by the time multiplexed pilot is also compared with that of the parallel pilot channel.

Multiple-symbol differential detection (DD) with reference signal estimation based on the feedback of past detected symbols is presented for differentially encoded 16-level amplitude/phase shift keying (16DAPSK). A suboptimal decision is derived. The approximate analysis of the bit-error rate (BER) performance taking into account the decision error propagation effect is presented in an additive white Gaussian noise (AWGN) channel and the BER performance is compared with those of 16DPSK and 16 quadrature amplitude modulation (16QAM).

An expression for the bit error rate (BER) of 16 STAR-QAM modulation with differential encoding and detection in a Rician fading channel with diversity reception is obtained. BER curves for various ratios of the line-of-sight power to the multipath power, Doppler frequencies and orders of diversity are presented. It is shown that 16 STAR-OAM outperforms 16 DPSK under the same power limited condition.

We present a new closed-form bit error probability formula for narrow-band FSK with limiter-discriminator-integrator detection in Rayleigh fading channels. This formula eliminates the tedious numerical integrations required in previous publications. The computed results are verified by experiment. We provide physical explanations, on how the system parameters such as fading, IF filter bandwidths and FM carrier frequency deviations affect the error performance, not previously available in the literature.>

A time diversity automatic repeat-request (ARQ) scheme with a finite number of transmissions is investigated for a digital FM mobile radio with frequency demodulation (FD). It processes all the retransmissions of a single data block using postdetection diversity combining. The analysis of the signal energy per bit required for a given bit error rate (BER) and the spectral efficiency in a cellular mobile radio system are presented. The results obtained from the numerical calculations show that this ARQ scheme offers a performance superior to both the basic ARQ scheme and the time-diversity scheme.>

An analysis of bit error rate (BER) in a binary digital FM system with postdetection diversity is presented. Expressions for the average BER due to additive white Gaussian noise (AWGN), random FM noise and delay-spread in the multipath channel are derived for reception using differential demodulation (DD), and frequency demodulation (FD) assuming independent fading signals. Calculated results for MSK show that the BER performance is strongly dependent on the RMS-delay/bit-duration ratio and that the delay-spectrum shape is of no importance when the receiver predetection filter product is optimized for the effect of AWGN. The effect of fading correlation on the diversity improvement is also analyzed for a two-branch case with multiplicative Rayleigh fading signals. Expressions for the average BER due to AWGN and random FM noise are derived. Calculated results are shown for the average BER due to random FM noise assuming a horizontally spaced antenna system at a mobile station. It is shown that the use of small antenna spacings leads to a diversity improvement greater than that obtainable for the case of independent AWGN.>

Random FM noise using two-branch selection combining with correlated Rayleigh fading signals is analyzed for land mobile radio systems. General expressions are derived for the cumulative distribution function and mean square value of the random FM noise; they can be applied to any type of diversity such as space, polarization, etc. Calculated results show that, if two horizontally spaced antennas parallel with the direction of vehicle motion are used at a mobile station, random FM noise can be significantly reduced for small antenna spacings.>