To accommodate the proliferation of Internet-of-Things (IoT) applications, next-generation wireless communication networks, particularly the sixth-generation (6G), are expected to offer excellent support for the massive access of machine-type communication (MTC). In this paper, we investigate the grant-free random access (GFRA) employing orthogonal preambles in cell-free massive multiple-input multiple-output (mMIMO), which shows immense potential for enabling massive connectivity. In particular, we take into account the capture effect, defined as successful decoding despite preamble collisions, when the received signal-to-interference-plus-noise ratio (SINR) exceeds a predefined threshold. To this end, we develop an analytical framework to model GFRA with the capture effect adopting stochastic geometry. Subsequently, approximate analytical expressions for the received SINR and the access success probability for the typical GFRA frame structure are derived. Furthermore, leveraging these theoretical expressions, we formulate an optimization problem to determine the optimal preamble length that maximizes effective throughput. Simulation results validate the accuracy of our theoretical analyses and demonstrate the superior access performance of the optimized frame structure, whereas a frame structure with a constant preamble length does not consistently attain maximum effective throughput across varying user densities.

As the Internet of Things (IoT) continues to expand and reshape our world, new vertical application scenarios have emerged, such as underwater communications, leading to increased interest in academia and industries. The multiple-input–multiple-output (MIMO) technology plays a critical role in enhancing channel capacity for underwater acoustic (UWA) communications, where accurate channel prediction is essential for system performance. In this article, we propose a novel efficient channel impulse response (CIR) prediction model for the UWA MIMO communications with a small adaptive bidirectional gated recurrent unit (ABiGRU) network. The proposed model can capture the channel information without additional knowledge of the internal properties of the channel itself. Moreover, it first utilizes preceding short-term CIR data from the channel estimation for online training, and then exploits the trained model for the CIR prediction, which tracks time-varying UWA channels. To verify the effectiveness of the predicted CIRs, we design a scheme combining a space-time block coding (STBC) and minimum mean square error (MMSE) pre-equalization for the UWA MIMO system. Our proposed STBC-MMSE pre-equalization scheme has demonstrated practical feasibility and low-bit-error rate (BER) in numerical simulations. In addition, we evaluate the prediction error performance of the proposed ABiGRU network through comparison with the widely used MMSE algorithm and two common recurrent neural networks (RNNs) predictors, i.e., the gated recurrent unit and long short term memory (LSTM) network. Finally, we conduct realistic in-field UWA MIMO experiments to demonstrate and justify the superiority of the proposed ABiGRU network, which can lay the solid foundation for cost-effective UWA MIMO communications for building promising underwater IoT sensor networks.

In this paper, we investigate the grant-based massive random access in cell-free (CF) massive multiple-input multiple-output (mMIMO) networks. A fixed cluster-based collision resolution random access (FCCRRA) protocol is proposed to mitigate severe pilot collisions for massive Internet of Things (IoT) by leveraging the difference in received power distribution across distributed access points (APs). Particularly, the cooperation among clustered APs and the enhanced normalized conjugate beamforming (ECB) are jointly exploited to achieve a low-complexity distributed contention resolution. Moreover, we derive the theoretical received power distribution of a user equipment (UE) across different APs and coverage areas and then formulate an optimization problem to determine a suitable parameter for fixed clustering. The results verify the superior performance of the proposed FCCRRA to benchmarks in terms of throughput and access success probability.

Channel modeling is crucial to the design and analysis of terahertz wireless communications. In this paper, we present a new channel model for RIS-assisted terahertz wireless channels, that includes scattering from rough surfaces in the channel environment. The main advantage of this model is giving useful insights into how the scattering of the environment’s objects can affect the performance of RIS units in terahertz communications. Also, the model can be used for efficient design and placement of RIS structure in the environment. Using the proposed model, a simple scenario has been analyzed and the channel impulse response (CIR) versus time and angle of departure is presented for the channel with different RIS positions.

The terahertz (THz) band is a promising frequency band that ranges from 0.3 THz to 10 THz and being considered for the next generation 6G wireless networks due to the large available bandwidth and potentially ultra fast data rates. THz channels and systems are unique in three aspects: 1) high path loss; 2) rich scattering from rough surfaces; 3) severe phase noise from local oscillators. These pose questions on what physical waveforms should be used in THz channels. Since orthogonal frequency division multiplexing (OFDM) and discrete Fourier transform spread OFDM (DFT-s-OFDM) are adopted waveforms in 5G new radio (NR) and 4G, their possible use in the future generation wireless networks is an open question. In this paper, we first review a THz channel model for accurate representation of THz channels. Then uncoded and coded OFDM and DFT-s-OFDM systems are investigated for their performance in THz channels, demonstrating their unique behaviors in these channels. The impact of phase noise is also examined, and a non-iterative compensation method slightly modified from the literature is used to mitigate the phase noise effect. DFT-s-OFDM shows advantages over OFDM in the studied THz environment. The simulation results in this paper can be used as a benchmark for future studies.

With the fifth-generation (5G) networks widely commercialized and fast deployed, the sixth-generation (6G) wireless communication is envisioned to provide competitive Quality of Service (QoS) in multiple aspects to global users. The critical and underlying research of 6G is, first, highly dependent on the precise modeling and characterization of the wireless propagation when the spectrum is believed to expand to the terahertz (THz) domain. Moreover, future networks’ power consumption and energy efficiency are critical factors to consider. In this research, based on a review of the fundamental mechanisms of reconfigurable intelligent surface (RIS)-assisted wireless communications, we utilize the 3-D ray-tracing method to analyze a realistic indoor THz propagation environment with the existence of human blockers. Furthermore, we propose a distributed RISs framework (DRF) to assist the indoor THz wireless communication to achieve overall energy efficiency. The numerical analysis of simulation results based on more than 2900 indoor THz wireless communication subscenarios has demonstrated the significant efficacy of applying distributed RISs to overcome the mobile human blockage issue, improve the THz signal coverage, and increase signal-to-noise ratios (SNRs) and QoS. With practical hardware design constraints investigated, we eventually envision how to utilize the existing integrated sensing and communication techniques to deploy and operate such a system in reality. Such a DRF can also lay the foundation of efficient THz communications for Internet of Things (IoT) networks.

With the increasing data traffic in the fifth-generation (5G) communication system, the 5G new radio extended to unlicensed bands (5G NR-U) has become a promising approach to relieve the heavy pressure on the cellular system. To achieve the efficient coexistence with the WiFi system and improve the efficiency of temporal, spectral and spatial resource utilization, we first divide the transmission space into two subspaces by leveraging spatial reuse, where the data transmitted by cellular user equipments (UEs) falls into one subspace and the data transmitted by Internet of Things (IoT) devices coexisting with WiFi users through power control is in the other subspace. Then, the coexistence among cellular UEs, IoT devices, and WiFi users is formulated as an optimization model with the aim of maximizing the cellular system throughput via the joint power and subchannel allocation under the interference constraint. Although the resulting optimization problem is a mixed-integer nonlinear programmming, we decompose it into two subproblems and develop an alternating iterative approach to effectively solve them. Also, the closed-form allocations of the power and subchannels are obtained. Simulation results confirm that the proposed scheme can improve the cellular system performance and guarantee the coexistence in the unlicensed band.

In this paper, we study a joint user pairing and power allocation problem in the 5th generation (5G) satellite random access (RA) networks, where some user equipments (UEs) are assisted by relay satellite UEs to establish satellite access. We aim to maximize the total sum rate of the RA system by jointly optimizing user pairing and power allocation. The above joint optimization problem is a non-convex mixed-integer problem, which is challenging to solve. To solve this problem, we decompose it into two subproblems. Firstly, a problem for optimal user pairing is formulated to find the optimal user pairing relationship. To solve this subproblem efficiently, a Q-learning based distributed user pairing algorithm (QL-DUPA) is proposed, which converts the user pairing problem to a Q-learning process. The Q-learning process can achieve a near-optimal solution and is practically feasible. Then, a problem for optimal power allocation is formulated to find the optimal power allocation coefficients in each user pair. The subproblem is convex and the optimal solution is obtained using convex optimization. Next, a satellite RA scheme with collision resolution is proposed based on the joint optimization of user pairing and power allocation, and we analyze its total sum rate. Simulation results show that the proposed satellite RA scheme with collision resolution greatly outperforms the existing schemes in terms of total sum rate.

In this article, we investigate deep-learning-based omni intrusion detection system (IDS) for supervisory control and data acquisition (SCADA) networks that are capable of detecting both temporally uncorrelated and correlated attacks. Regarding the IDSs developed in this article, a feedforward neural network (FNN) can detect temporally uncorrelated attacks at an F1 of 99.967±0.005% but correlated attacks as low as 58±2%. In contrast, long short-term memory (LSTM) detects correlated attacks at 99.56±0.01% while uncorrelated attacks at 99.3±0.1%. Combining LSTM and FNN through an ensemble approach further improves the IDS performance with F1 of 99.68±0.04% regardless the temporal correlations among the data packets.

The fifth-generation (5G) and beyond networks are designed to efficiently utilize the spectrum resources to meet various quality of service (QoS) requirements. The unlicensed frequency bands used by WiFi are mainly deployed for indoor applications and are not always fully occupied. The cellular industry has been working to enable cellular and WiFi coexistence. In particular, 5G New Radio in unlicensed channel spectrum (NR-U) supports the uplink and downlink transmission on the maximum channel occupation time (MCOT) duration. In this paper, we consider maximizing the total throughput of both downlink and uplink in NR-U by jointly optimizing the time and power allocation during MCOT while ensuring fair coexistence with WiFi. Fairness is guaranteed in two steps: 1) tuning the access related parameters of NR-U to achieve proportional fairness, and 2) including 3GPP fairness from the throughput perspective as a constraint in NR-U throughput maximization. Numerical analysis and simulation have demonstrated the superior performance of the proposed resource allocation algorithm compared to conventional deployment strategies.

Cellular vehicle‐to‐everything‐ (C‐V2X‐) based communications can support various content‐oriented applications and have gained significant progress in recent years. However, the limited backhaul bandwidth and dynamic topology make it difficult to obtain the multimedia service with high‐reliability and low‐latency communication in C‐V2X networks, which may degrade the quality of experience (QoE). In this paper, we propose a novel cluster‐based cooperative cache deployment and coded delivery strategy for C‐V2X networks to improve the cache hit ratio and response time, reduce the request‐response delay, and improve the bandwidth efficiency. To begin with, we design an effective vehicle cluster method. Based on the constructed cluster, we propose a two‐level cooperative cache deployment approach to cache the frequently requested files on the edge nodes, LTE evolved NodeB (eNodeB) and cluster head (CH), to maximize the overall cache hit ratio. Furthermore, we propose an effective coded delivery strategy to minimize the network load and the ratio of redundant files. Simulation results demonstrate that our proposed method can effectively reduce the average response delay and network load and improve both the hit ratio and the ratio of redundant files.

Image based localization is a key block of visual simultaneous localization and mapping (SLAM) system where image data is used to localize the camera relative to an arbitrary reference frame. Although finding the location from one image or between two images is well studied in the literature, few works study the problem of finding the pose of multiple images in videos of different frame lengths. Here, we propose two different architectures to address this problem, one using a combination of 2D convolutional neural network (CNN) and recurrent neural networks (RNN) and the other using 3D CNN. We demonstrate that 3D CNN is better for pose estimation problem than CNN-RNN by visualizing the learned features per layer of both architectures and the accuracy performance. Further, instead of using RGB images as input to the networks, we use SURF descriptors to reduce the image dimension of 480×640×3 by more than 48 folds, making the training time much faster and the learning model less complex. Both architectures show competitive performance in comparison to the state of the art on indoor localization dataset with the ability to generalize to test scenes that are completely different from the training scenes.

We propose SURF-LSTM, a low complexity deep architecture to learn image absolute pose (position and orientation) in indoor environments using SURF descriptors and recurrent neural networks. Given the strongest SURF features descriptors of an input image, we use 2 layers of bidirectional long short term memory (LSTM) to model the sequential relation between them to learn the 6 degrees of freedom absolute pose in an arbitrary reference frame. In addition to achieving competitive performance compared to existing image localization methods, our system can be trained in less than 10 minutes instead of hours by the state of the art. It requires as small as 0.0128 MB to save the image frame rather than 0.08 MB compared to other methods that use the cropped images and the weights file needs 1.5 MB of storage compared to 100 MB of other methods which leads to significant time and space efficiency.

Neural networks-based camera pose estimation systems rely on fine tuning very large networks to regress the camera position and orientation with very complex training procedure. In this paper, we explore the following question: do we need to fine tune and train such complex networks to reach the desired accuracy? We show that we can reach comparable or better accuracy for the single image indoor localization systems with using only one layer of ridge regression and pretrained features of ResNet-50 architecture with training time less than a second on CPU instead of hours of GPU training needed by the state of the art. For outdoor scenes, we show that using only 3 fully connected layers on top of pretrained ResNet50 features without fine-tuning can perform well compared to the state of the art with only minutes of training. For more complexity reduction, we show that downsampling the pretrained ResNet-50 features by more than 10 times using principal component analysis (PCA) has a little effect on the performance but can save both training time and storage space.

As 5G wireless systems and networks are now being globally commercialized and deployed, more diversified application scenarios are emerging, quickly reshaping our societies and paving the road to the beyond 5G (6G) era when terahertz (THz) and unmanned aerial vehicle (UAV) communications may play critical roles. In this paper, aerial channel models under multiple meteorological conditions such as rain, fog and snow, have been investigated at frequencies of interest (from 2 GHz to 900 GHz) for UAV communications. Furthermore, the link budget and the received signal-to-noise ratio (SNR) performance under the existing air-to-ground (A2G) channel models are studied with antenna(s) system considered. The relationship between the 3D coverage radius and UAV altitude under the influence of multiple weather (MW) conditions is simulated. Numerical results show that medium rain has the most effects on the UAV's coverage for UAV communications at millimeter wave (mmWave) bands, while snow has the largest impacts at near THz bands. In addition, when the frequency increases, the corresponding increase in the number of antennas can effectively compensate for the propagation loss introduced by weather factors, while its form factor and weight can be kept to maintain the UAV's payload.

In this paper, we propose a new transmit power diversity scheme for contention resolution diversity slotted ALOHA (CRDSA) under total transmit power limitation in satellite networks. In the proposed scheme, the total transmit power of each device within a frame is considered to be the same, and allocated to multiple packet replicas, and the transmit power of each packet replica can be different, which enables the transmit power diversity. The threshold based capture model is employed at the gateway demodulator, and the recovery-error probability based on this model is derived. The threshold of capture and transmit powers of packet replicas are also jointly optimized to maximize the achievable sum rate (ASR) of CRDSA under total transmit power limitation. Simulation results show that the proposed scheme is more than 50% higher than the conventional one in terms of normalized ASR.

Unmanned aerial vehicle (UAV)-assisted communications is a promising solution to improve the performance of future wireless networks, where UAVs are deployed as base stations for enhancing the quality of service (QoS) provided to ground users when traditional terrestrial base stations are unavailable or not sufficient. An effective framework is proposed in this paper to manage the dynamic movement of multiple unmanned aerial vehicles (UAVs) in response to ground user mobility, with the objective to maximize the sum data rate of the ground users. First, we discuss the relationship between the air-to-ground (A2G) path loss (PL) and the location of UAVs. Then a deep Q-network (DQN) based method is proposed to adjust the locations of UAVs to maximize the sum data rate of the user equipment (UE). Finally, simulation results show that the proposed method is capable of adjusting UAV locations in a real-time condition to improve the QoS of the entire network.

The authors introduce a novel hybrid precoding algorithm based on Gram–Schmidt orthogonalisation (GSO) in millimetre‐wave massive MIMO systems. Specifically, the columns of array response matrix orthogonalised by the GSO process are considered as a set of candidate analogue precoders, then traditional orthogonal matching pursuit (OMP) is utilised to find the optimal analogue and digital precoders. Since GSO is a recursive process that depends on the order in which the matrix columns are selected. A heuristic solution to the order of columns selection is suggested according to the array response vector along which the fully‐digital precoder has the maximum projection. The proposed algorithm, not only constrained to uniform linear arrays, can avoid the matrix inversion in designing the digital precoder compared to OMP. Simulation results show that the spectral efficiency and bit error rate of the proposed hybrid precoding solutions are close to that obtained with fully digital architectures. Furthermore, the results indicate that the proposed hybrid precoding solutions outperform the orthogonality‐based matching pursuit, which uses the columns of the DFT matrix as a set of candidate analogue precoders.

The rapid advancement of Internet of Things (IoT) and fifth generation and beyond technologies is transforming the marine industry and research. Our understanding of the vast sea that covers 71% of the Earth's surface is being enhanced by the various ocean sensor networks equipped with effective communication technologies. In this article, we begin with a review of the research and development status-quo of Maritime IoT (MIoT) enabled by multiple wireless communication technologies. Then, we study the impact of sea waves on radio propagation and the communications link quality. Due to the severe attenuation of sea water to radio-frequency electromagnetic wave propagation, large ocean waves can easily block the communication link between a buoy sensor and a cell tower near shore. This article for the first time uses the ocean wave modeling of coastal and oceanic waters to examine the condition of line-of-sight communications. Real wave measurement data parameters are applied in the numerical evaluation of the developed model. Finally, the critical antenna design taking into account the wave impact is numerically studied with implementation solutions proposed, and the system hardware and protocol aspects are discussed.

Unmanned aerial vehicle (UAV)-assisted communication is a promising technology in future wireless communication networks. UAVs can not only help offload data traffic from ground base stations (GBSs) but also improve the Quality of Service (QoS) of cell-edge users (CEUs). In this article, we consider the enhancement of cell-edge communications through a mobile relay, i.e., UAV, in multicell networks. During each transmission period, GBSs first send data to the UAV, and then the UAV forwards its received data to CEUs according to a certain association strategy. In order to maximize the sum rate of all CEUs, we jointly optimize the UAV mobility management, including trajectory, velocity, and acceleration, and association strategy of CEUs to the UAV, subject to minimum rate requirements of CEUs, mobility constraints of the UAV, and causal buffer constraints in practice. To address the mixed-integer nonconvex problem, we transform it into two convex subproblems by applying tight bounds and relaxations. An iterative algorithm is proposed to solve the two subproblems in an alternating manner. Numerical results show that the proposed algorithm achieves higher rates of CEUs as compared with the existing benchmark schemes.

In this article, we propose an optimal irregular repetition slotted ALOHA (IRSA) under total transmit power constraint for random access (RA) in the Internet-of-Things (IoT)-oriented satellite networks, which is named as an optimal power-limited IRSA (PL-IRSA). In this proposal, the total transmit power for each satellite machine-type device (SMD) within a frame is considered to be the same and equally allocated into its multiple packet replicas. Due to a variant number of packet replicas, the transmit power of each packet replica for different SMDs may be different. The difference of transmit powers of packet replicas and path loss enhance the received power diversity, which is able to improve the throughput by using the capture effect. At the receiver side, we introduce a semi-analytical (SEA) model to approximate the physical-layer decoding and derive an asymptotic packet loss rate (PLR) based on this SEA model. From the derived results, an optimization problem is formulated and solved to find out the optimal degree distributions for different total transmit powers and code rates, which maximize the normalized system throughput. The simulation results demonstrate that the proposed optimal PL-IRSA can lead to significant performance improvement with respect to conventional ones.

Distributed phased arrays based multiple-input multiple-output (DPA-MIMO) is a recently proposed highly reconfigurable architecture enabling both spatial multiplexing and beamforming in millimeter-wave (mmWave) systems. In this work, we focus on coping with the hybrid precoding for the wideband DPA-MIMO system with orthogonal frequency division multiplexing (OFDM) modulation. More specifically, we propose an alternating direction method of multipliers (ADMM) enabled hybrid precoding approach based on an alternating optimization framework, abbreviated to ADMM-AltMin, for such cooperative array-of-subarrays structures. Simulation results show that the proposed ADMM-AltMin method achieves favourable performance with practical quantization of phase shifters taken into account.

Millimeter-wave (mmWave), massive multiple-input multiple-output (MIMO), are expected to play a crucial role for 5G and beyond cellular and next-generation wireless local area network (WLAN) communications. Moreover, unmanned aerial vehicles (UAVs) are also considered as an important component of next-generation networks. In this paper, we propose and present a mmWave distributed phased-arrays (DPA) architecture and proof-of-concept (PoC) designs for user equipment (UE) and unmanned aerial vehicles (UAVs) which will be used in 5G/Beyond 5G wireless communication networks. Through enabling a multi-stream multi-beam communication mode, the UE PoC achieves a peak downlink speed of more than 4 Gbps with optimized thermal distribution performance. Furthermore, based on the DPA topology, the UAV aerial base station (ABS) prototype is designed and demonstrates for the first time an aggregated peak downlink data rate of 2.2 Gbps in the real-world field tests supporting multi-user (MU) application scenarios.

This study examines the linear source and relay precoder and destination combiner design for multiple‐input multiple‐output full‐duplex (FD) relay communication systems. The effect of the residual interference due to the imperfect loop interference cancellation is considered in the design. Two design algorithms are proposed to minimise the mean squared error of the received signal at the destination. The first is a tri‐step alternating iterative algorithm while the second is a bi‐step iterative algorithm, which has lower complexity and performance comparable to that of the first algorithm. The convergence of these algorithms is evaluated. Results are presented, which show that the proposed FD relay system can provide approximately double the achievable rate of the corresponding half‐duplex system if the residual interference is not high.

This article proposes recurrent neural networks (RNNs) for the WiFi fingerprinting indoor localization. Instead of locating a mobile user's position one at a time as in the cases of conventional algorithms, our RNN solution aims at the trajectory positioning and takes into account the correlation among the received signal strength indicator (RSSI) measurements in a trajectory. To enhance the accuracy among the temporal fluctuations of RSSI, a weighted average filter is proposed for both input RSSI data and sequential output locations. The results using different types of RNN, including vanilla RNN, long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional RNN (BiRNN), bidirectional LSTM (BiLSTM), and bidirectional GRU (BiGRU) are presented. On-site experiments demonstrate that the proposed structure achieves an average localization error of 0.75 m with 80% of the errors under one meter, which outperforms K-nearest neighbors algorithms and probabilistic algorithms by approximately 30% under the same test environment.

Unmanned aerial vehicles (UAVs) for wireless communications have rapidly grown into a research hotspot as the mass production of high-performance, low-cost, and intelligent UAVs becomes practical. In the meantime, the fifth generation (5G) wireless communication and Internet-of-Things (IoT) technologies are being standardized and planned for global deployment. During this process, UAVs are becoming an important part of 5G and IoT, and expected to play a crucial role in enabling more functional diversity for wireless communications. In this paper, we first present a summary of mainstream UAVs and their use in wireless communications. Then, we propose a hierarchical architecture of UAVs with multilayer and distributed features to facilitate the integration of different UAVs into the next-generation wireless communication networks. Finally, we unveil the design tradeoffs with the consideration of power transfer, wireless communication, and aerodynamic principles. In particular, empirical models and published measurement data are used to analyze power transfer efficiency, and meteorological impacts on UAVs enabled next-generation wireless communications.

This paper presents a hybrid channel estimator for multiple-input multiple-output orthogonal frequency-division multiplexing mmWave systems based on the sparse nature of the angular channel and leveraging the compressed sensing (CS) tools. The angular support is recovered without any discretization by treating the angular channel in a continuous framework which resolves the limited angular resolution of the discrete sparse channel models used in the previous CS-based channel estimators. The power leakage problem is also addressed by modeling the continuous angular channel as a multi-band signal with the bandwidth of each sub-band being proportional to the amount of power leakage caused by the limited antenna array length. The RF combiner is implemented using a network of low-power switches for antenna subset selection based on a multi-coset sampling pattern. Simulation results validate the low reconstruction error and good performance of the proposed channel estimator.

Predicting channel state information (CSI) is a fundamental element in wireless communications systems. An accurate CSI estimation and prediction is critical to the system performance. This paper introduces a recurrent neural network (RNN) based approach for real-time prediction in real-world non-stationary channels. It uses the recent history data for online training, followed by prediction employing the trained model, in order to adapt to the changing channel and obtain a more accurate CSI prediction compared to conventional methods. Furthermore, the proposed method needs no additional knowledge, such as the internal properties of the channel itself, or the external features that affect the channel propagation, greatly facilitating its use in practical systems. Simulation results show that the proposed adaptive and parameter free recurrent neural structure (APF-RNS) outperforms the existing methods under a dynamically changing non-stationary environment. Therefore, the proposed online training based RNN approach is a promising method for channel prediction in wireless communications.

We investigate a general channel estimation problem in the massive multiple-input multiple-output system which employs the hybrid analog/digital precoding structure with limited radio-frequency (RF) chains. By properly designing RF combiners and performing multiple trainings, the proposed channel estimation can approach the performance of fully-digital estimations depending on the degree of channel spatial correlation and the number of RF chains. Dealing with the hybrid channel estimation, the optimal combiner is theoretically derived by relaxing the constant-magnitude constraint in a specific single-training scenario, which is then extended to the design of combiners for multiple trainings by sequential and alternating methods. Further, we develop a technique to generate the phase-only RF combiners based on the corresponding unconstrained ones to satisfy the constant-magnitude constraints. The performance of the proposed hybrid channel estimation scheme is examined by simulations under both nonparametric and spatial channel models. The simulation results demonstrate that the estimated channel state information can approach the performance of fully-digital estimations in terms of both mean square error and spectral efficiency. Moreover, a practical spatial channel covariance estimation method is proposed and its effectiveness in hybrid channel estimation is verified by simulations.

In this paper, we study the hybrid precoding structures over limited feedback channels for massive multiuser multiple-input multiple-output (MIMO) systems. We focus on the system performance of hybrid precoding under a more realistic hardware network model, particularly, with inevitable dissipation. The effect of quantized analog and digital precoding is characterized. We investigate the spectral efficiencies of two typical hybrid precoding structures, i.e., the sub-connected structure and the fully connected structure. It is revealed that increasing signal power can compensate for the performance loss incurred by quantized analog precoding. In addition, by capturing the nature of the effective channels for hybrid processing, we employ a channel correlation-based codebook and demonstrate that the codebook shows a great advantage over the conventional random vector quantization codebook. It is also discovered that, if the channel correlation-based codebook is utilized, the sub-connected structure always outperforms the fully connected structure in either massive MIMO or low signal-to-noise ratio scenarios; otherwise, the fully-connected structrue achieves better performance. Simulation results under both Rayleigh fading channels and millimeter wave (mm-wave) channels verify the conclusions above.

In this paper, we study the hybrid precoding structures for massive multiuser multiple-input multiple-output (MIMO) systems. Particularly, the practical hardware network models with insertion loss are developed. The achievable rates of two typical hybrid precoding structures, the fully-connected structure and the sub- connected structure, are investigated, from which we discover that the sub-connected structure always outperforms the fully-connected structure in terms of the achievable rate in massive MIMO. We further characterize the effect of quantized analog precoding which indicates that the subconnected structure is able to achieve better performance with fewer feedback bits than the fully-connected structure. We also propose a channel statistics-based codebook used for the digital precoding stage which is more suitable for hybrid precoding systems than the conventional random vector quantization (RVQ) codebook.

In this letter, a multiuser relay network with massive multiple-input multiple-output is investigated with mixed-analog-to-digital converter (ADC) at receiver. We first characterize the uplink achievable rate by deriving a tight approximation, which embraces the conventional unquantized system as a special case. Both power scaling laws at sources and relay are presented. It is validated that the performance loss due to low-precision ADCs can be compensated by increasing the number of antennas M, obeying a logarithmical scaling law, rather than by increasing the transmit power at sources and/or relay. We show that the performance suffers from a loss factor interpreted as a nominal effective resolution of the entire mixed-ADC structure. Simulation results verify our observations.

Considering a heterogeneous network where both macro base station (BS) and small cell (SC) nodes are equipped with massive number of antennas, this paper studies the performance for multiple-input multiple-output downlinks when the macro and small cells share the same spectrum, and hence interfere with each other. Suppose that the large-scale antenna arrays at both macro BS and SC nodes employ maximum-ratio transmission (MRT) or zero-forcing transmission (ZFT) precoding, and transmit data streams to served users simultaneously. A new pilot reuse pattern among SCs is proposed for channel estimation. Taking into account imperfect channel state information (CSI), capacity lower bounds for MRT and ZFT are derived, respectively, in closed-form expressions involving only statistical CSI, followed by asymptotic analyses for massive arrays under specific power scaling laws. Subsequently, two user scheduling algorithms, greedy scheduling and asymptotical scheduling algorithm (ASA), are proposed based on derived capacity lower bounds and asymptotic analyses, respectively. ASA is demonstrated to be a near optimal in the asymptotic regime and has low complexity. Finally, the derived closed-form expressions are verified to be accurate predictors of the system performance by Monte Carlo simulations. Numerical results demonstrate the effectiveness of the asymptotic analysis and proposed user scheduling schemes.

We consider a multi-pair massive multiple-input multiple-output relay network, where the relay is equipped with a large number, N, of antennas, but driven by a far smaller number, L, of radio-frequency (RF) chains. We assume that K pairs of users are scheduled for simultaneous transmission, where K satisfies 2K=L. A hybrid signal processing scheme is presented for both uplink and downlink transmissions of the network. Analytical expressions of both spectral efficiency (SE) and energy efficiency (EE) are derived with respect to the RF chain number under imperfect channel estimation. It is revealed that, under the condition N>⌊4L2/π⌋, the transmit power of each user and the relay can be, respectively, scaled down by 1/√N and 2K/√N if pilot power scales with signal power, or they can be, respectively, scaled down by 1/N and 2K/N if the pilot power is kept fixed, while maintaining an asymptotically unchanged SE. While regarding EE of the network, the optimal EE is shown to be achieved when Pr= 2K Ps, where Prand Ps, respectively, refer to the transmit power of the relay and each source terminal. We show that the network EE is a quasi-concave function with respect to the number of RF-chains which, therefore, admits a unique globally optimal choice of the RF-chain number. Numerical simulations are conducted to verify our observations.

We propose a pilot-data transmission overlay scheme for multipair massive multiple-input multiple-output (MIMO) relaying systems employing either half-duplex or full-duplex (FD) communications at the relay station (RS). In the proposed scheme, pilots are transmitted in partial overlap with data to decrease the channel estimation overhead. The RS can detect the source data with minimal destination pilot interference by exploiting the asymptotic orthogonality of massive MIMO channels. Then pilot-data interference can be effectively suppressed with the assistance of the detected source data in the destination channel estimation. Due to the transmission overlay, the effective data period is extended, hence improving system throughput. Both theoretical and simulation results confirm that the proposed pilot-data overlay scheme outperforms the conventional separate pilot-data design in the limited coherence interval scenario. Moreover, at asymptotically high and low SNR regions, the proposed scheme is superior regardless of the coherence interval length. Because of simultaneous transmission, the proper power allocation of source data transmission and relay data forwarding can further improve the system performance. Hence a power allocation problem is formulated and a successive convex approximation approach is proposed to solve the non-convex optimization problem with the FD pilot-data transmission overlay.

Weighted autocorrelation receivers have been proposed in the literature to suppress noise or interference for transmitted reference ultra-wideband communication systems. Usually weight optimization is performed for partitioned integration bins. To improve the optimization effect, this paper proposes a digital weighted autocorrelation receiver, in which the sampled auto-correlated signal is first rearranged following a channel characteristic vector that sorts the strengths of the received channel samples, and then it is divided into multiple partitions. Finally, the integration bins corresponding to these partitions are weighted according to the minimum mean square error principle. Results show that compared to the digital versions of existing weighted autocorrelation receivers, the proposed digital scheme can achieve significantly better bit error rate performance with limited penalty in terms of implementation complexity.

We consider a multi-pair massive multiple-input multiple-output (MIMO) two-way relay network, where multiple pairs of single-antenna users exchange data with the help of a multi-antenna relay station. We assume that the relay is equipped with a large antenna array, but driven by a far smaller number of RF chains, which can enormously reduce the hardware cost and complexity for practical applications. We propose a hybrid precoding scheme for both uplink and downlink of the network and analyze the sum rate performance under imperfect channel estimate. Numerical results verify that the proposed scheme incurs limited degradation compared to traditional full-dimensional digital precoding. Given the relationship between the number of relay antennas, N, and the RF chain number, L, satisfying N > 4L2/π, we further discover that the transmit power of each user and the relay can be respectively scaled down by a factor of 1 /√N and L/√N if the pilot power scales with the signal power, or by a factor of 1/N and L/N if the pilot power is kept fixed, while maintaining an asymptotically unchanged performance.

For a massive multiple-input multiple-output (MIMO) system, restricting the number of RF chains to far less than the number of antenna elements can significantly reduce the implementation cost compared to the full complexity RF chain configuration. In this paper, we consider the downlink communication of a massive multiuser MIMO (MU-MIMO) system and propose a low-complexity hybrid block diagonalization (Hy-BD) scheme to approach the capacity performance of the traditional BD processing method. We aim to harvest the large array gain through the phase-only RF precoding and combining and then digital BD processing is performed on the equivalent baseband channel. The proposed Hy-BD scheme is examined in both the large Rayleigh fading channels and millimeter wave (mmWave) channels. A performance analysis is further conducted for single-path channels and large number of transmit and receive antennas. Finally, simulation results demonstrate that our Hy-BD scheme, with a lower implementation and computational complexity, achieves a capacity performance that is close to (sometimes even higher than) that of the traditional high-dimensional BD processing.

In this paper, we consider a multi-pair two-way amplify-and-forward relaying system where multiple sources exchange information via a relay node equipped with large-scale antenna arrays. Given that channel estimation is non-ideal, and that the relay employs either maximum-ratio combining/maximum-ratio transmission (MRC/MRT) or zero-forcing reception/zero-forcing transmission (ZFR/ZFT) beamforming, we derive two corresponding closed-form lower bound expressions for the ergodic achievable rate of each pair sources. The closed-form expressions enable us to design an optimal power allocation (OPA) scheme that maximizes the sum spectral efficiency under certain practical constraints. As the antenna array size tends to infinity and the signal-to-noise ratios become very large, asymptotically OPA schemes in simple closed-form are derived. The capacity lower bounds are verified to be accurate predictors of the system performance by simulations, and the proposed OPA outperforms equal power allocation (EPA). It is also found that in the asymptotic regime, when MRC/MRT is used at the relay and the link end-to-end large-scale fading factors among all pairs are equal, the optimal power allocated to a user is inverse to the large-scale fading factor of the channel from the user to the relay, while OPA approaches EPA when ZFR/ZFT is adopted.

Considering a heterogeneous network (HetNet) where both macro base station (BS) and small cell (SC) nodes are equipped with large-scale antenna arrays, this paper studies the performance of the BS and SC multiple-input multiple-output (MIMO) downlink systems when the macro and small cells share the same spectrum and hence interfere with each other. Suppose that the large-scale antenna arrays at both macro BS and SC nodes employ maximum-ratio transmission (MRT) precoding and then transmit data streams to their served users simultaneously. Taking into account imperfect channel state information (CSI) obtained by channel estimation, downlink capacity lower bounds for a user in the macro cell and for a user in a small cell are derived as closed-form expressions involving only statistical CSI. Then, two user scheduling algorithms are proposed according to the derived lower bounds. The closed-form expressions for the achievable rates are verified to be accurate predictors for the system performance by Monte-Carlo simulations. Furthermore, numerical results demonstrate the effectiveness of the proposed user scheduling schemes.

Energy harvesting is an increasingly attractive source of power for wireless communications devices. In this paper, we consider a point-to-point (P2P) wireless communications system, where both the practical transmitter and receiver, whose hardware circuits consume non-zero power when active, are powered solely by the energy harvested from external sources. An energy cooperation save-then-transmit (EC-ST) scheme is proposed: both the transmitter and receiver go into sleep mode to save energy for a proportion of time while their passive energy harvester units collect energy for later operations, and then become active to communicate for the remaining time proportion (referred to as the active-ratio), during which energy is allowed to flow between the transmitter and receiver. We first consider additive white Gaussian noise one-way channels with two-way energy transfer under a deterministic energy arrival rate. In this case, the optimal active-ratio and the energy cooperation power are obtained in closed form to achieve the maximum throughput. Next, for Rayleigh block fading channels with a stochastic energy arrival rate, we find the optimal energy cooperation power for minimizing the outage probability. Finally, numerical and simulation results are presented to validate the analytical findings.

In this paper, physical-layer network coding (PNC) aided bi-directional cooperative relay strategies are proposed for four-node transmitted reference pulse cluster (TRPC) ultrawideband (UWB) systems, which can improve the network throughput and accomplish information exchange within two time slots instead of four. First, we develop a new detector and a link quality indicator (LQI) at the relay side according to the TRPC receiver structure. In view of the definition of LQI, two cooperative relay strategies are proposed, compared with the direct relay combining (RC) which needs three time slots. Simulation results show that the proposed PNC aided two-way relay schemes can improve the network throughput by a factor up to two in comparison to network coding (NC) aided schemes, and achieve better BER performance than the conventional RC.

Network densification with small cells has been recognized as the key mechanism in addressing the unremitting traffic growth over the next decade. This hierarchical network paradigm is characterized by highly fluctuating traffic demand, vast amount of signaling exchange, as well as progressively intensified resource under-utilization owing to service asymmetry. A flexible backhaul framework is imperative to cope with the above-mentioned challenges. In this paper, we introduce a novel wireless backhaul framework for future small cell networks (SCNs) with a new backhauling component, referred to as Type-A relay. This network entity offers increased architectural flexibility as well as substantial throughput enhancement over the existing LTE relaying-based solutions. Implementation challenges are discussed and potential solutions are provided. Simulation results are presented to demonstrate the strong potential of Type-A relay in future SCNs.

This paper presents the receiver design of a passband transmitted reference pulse cluster (TRPC) ultra-wideband (UWB) communication system and analyzes its bit error probability (BEP) in the presence of phase noise inherent in local oscillators. Based on a unified model of phase noisy oscillators, a theoretical BEP expression is obtained to evaluate the impact of phase noise on the BEP performance of TRPC-UWB communications in dense multipath channels. Semi-analytical results are also presented and discussed under the realistic IEEE 802.15.4a channel models.

The relay technology is effective in extending radio coverage and improving the performance of cell edge users. In multi-antenna relay channels, good knowledge of the channel state information (CSI) at the transmitter is important to achieve multiplexing gains of the multiple-input multiple-output technique. In this paper, we study the multi-antenna relay downlink channel with limited feedback CSI from both two-hop links. Data streams from the base station (BS) are first transmitted to a relay station (RS) with singular value decomposition-based precoding and receiver pulse shaping at the BS and RS, respectively. The block diagonalization precoding is then applied at the RS to forward the received signals to the remote multi-antenna users. We derive an upper bound for the system throughput loss due to CSI quantization error, and then propose a feedback quality control strategy to maintain a bounded rate loss relative to the perfect CSI case. It reveals that the feedback size B_1 from the RS to BS needs to scale in proportion to both transmit power at the BS and RS while the feedback size B_2 from each user to the RS only needs to scale linearly with the transmit power at the RS.

This paper considers the application of compressed sensing (CS) to a wireless sensor network for data measurement communication and reconstruction, where N sensor nodes compete for medium access to a single receiver. Sparsity of the sensor data in three domains due to time correlation, space correlation and multiple access are being utilized. We first provide an in-depth analysis on the CS-based medium access control schemes from a physical layer perspective and reveal the impact of communication signal-to-noise ratio on the reconstruction performance. We show the process of the sensor data converted to the modulated symbols for physical layer transmission and how the modulated symbols being recovered via compressed sensing. This paper further identifies the decision problem of distinguishing between active and inactive transmitters after symbol recovery and shows a comprehensive performance comparison between carrier sense multiple access and the proposed CS-based scheme. Second, a network data recovery scheme that exploits both spatial and temporal correlations is proposed. Simulation results validate the effectiveness of the proposed method in terms of communication throughput and show that enhanced performance can be obtained by utilizing the sensed signal's temporal and spatial correlations.

Maximizing the sum rate of a wireless network with multiple interfering links is an important and challenging problem in communication systems. This difficult non-convex problem has been approached from both an algorithmic perspective to achieve global optimality (e.g., using d.c. programming) and a relaxation perspective to obtain approximate solutions (e.g., high signal-to-noise-ratio approximation, binary power control, network symmetry, game-theoretic reformulation, etc.). It is generally agreed that 1) the global algorithms suffer from scalability issues and are more appropriate for problems of small instances; and 2) the solutions obtained based on maximizing the instantaneous performance are most likely suboptimal in practical fading wireless networks. In this work, we demonstrate that the sum rate can be efficiently optimized using the tool of stochastic geometry. In particular, we show that the average network sum rate can be derived in closed-form, taking into account both the random spatial distribution of the transmitters and the random Nakagami channel fading. An optimal contention density is further derived, which indicates the optimal number of supportable concurrent transmissions that attains the maximal sum rate. We discuss several applications of the derived results in interference-limited wireless systems.

Compressed sensing can be utilized in multiple access to save channel resource and power consumption to realize green communications. This paper considers the application of compressed sensing to a wireless sensor network for data measurement reconstruction collected in a natural environment. We consider a network with N sensor nodes, sharing a wireless channel with M degrees of freedom, and compete for medium access to a single receiver. A multiple access scheme based on multi-dimensional compressed sensing is proposed, which exploits spatial and time correlations that exist in natural signals. The proposed scheme further removes the necessity of conveying identity information, which improves system power efficiency and enhances system security. Simulation results validate the effectiveness of the proposed method in utilizing the sensed signal's time and spatial correlations to obtain enhanced performances.

Transmitted reference pulse cluster (TRPC) signalling was recently proposed for robust low-rate ultra-wideband (UWB) communications. TRPC provides significant performance gains over conventional transmitted reference (TR) UWB, and overcomes the critical long delay line problem associated with TR UWB. Thus, it is suited for practical implementation of a UWB communication system. The compact spacing of the pulses in TRPC leads to inter-pulse interference (IPI). In this study, the authors show that there exists an asymmetry between the two conditional distributions of the autocorrelation decision variable because of this IPI. This implies that the conventional zero decision threshold (ZDT) is not optimal for a TRPC autocorrelation receiver, and hence the authors derive the optimal maximum likelihood decision threshold. The authors propose two practical techniques for threshold determination. The first technique employs a training sequence whereas the other simply uses the decision variables of the received data signals to estimate the threshold. Simulation results show that in terms of the bit error rate (BER) performance, both the training-assisted adaptive decision threshold (TA-ADT) and the data-assisted ADT (DA-ADT) can achieve significant gains over the conventional ZDT-based detection for TRPC.

In cooperative orthogonal frequency division multiplexing (OFDM) systems, accurate frequency synchronization is critical to achieving any potential gains brought by the cooperative operation. The carrier frequency offsets (CFOs) present among multiple nodes (source, relays and destination) are more difficult to tackle than the single CFO problem in point-to-point systems. Multiple CFOs cause phase drift, inter-carrier interference (ICI) and inter-block interference (IBI) in the received signal. This paper deals with the CFO induced interference mitigation problem in distributed space time block coded (STBC) amplify-and-forward (AF) cooperative OFDM systems. We propose a two step approach to recover the phase distortion and suppress the ICI and IBI using low complexity methods to achieve high performance. The first step is time domain (TD) compensation and the second step is frequency domain (FD) decoding. Two TD compensation schemes are proposed, i.e., IBI-removal and ICI-removal. The IBI-removal scheme decouples the two blocks of one STBC codeword completely and then decodes the ICI degraded blocks individually. The ICI-removal scheme removes ICI first and the subsequent decoding requires joint decoding of the two blocks. Simulation results show that the IBI-removal scheme which is of lower complexity performs well with small CFO. For large CFO, the ICI-removal with modified iterative joint maximum likelihood decoding (MIJMLD) outperforms other schemes.

The problem of distributed power allocation for an interference relay network is considered, where multiple source-relay-destination (S-R-D) links communicate concurrently in the same frequency and interfere over two hops, referred to as a two-hop interference channel. The direct source-destination connections are not considered in this work. Power allocation in this scenario is challenging as it necessitates not only performance tradeoff among multiple links but also power distribution for each link along spatial dimensions. We approach the problem from a game-theoretic perspective and propose a novel implicit-based approach to prove the uniqueness of the Nash equilibrium (NE). This technique complements the existing literature on equilibria analysis by revealing the benefits of expressing the best responses in implicit forms. To benchmark the performance of the NE, we have investigated the non-convex sum-utility maximization problem, and have (1) identified the optimal solution structures; (2) proved that linear pricing is locally optimal in maximizing the sum utilities. A simple and distributed pricing algorithm is then proposed. Simulation results show that for a two-user network, the proposed scheme closely approaches the optimal sum rate, while, for a ten-user network, the improvement is up to 340% compared to the non-cooperative game model without pricing.

This paper considers the problem of resource allocation for a large-scale wireless network consisting of multiple amplify-and-forward cooperative systems. The traditional competitive design leads to a network collapse where every system obtains almost zero throughput. We resolve this issue by resorting to the novel economic model of coalition formation with externalities by first letting the systems (modeled as players) self-organize into mutually beneficial coalitions, followed by a sequential non-cooperative game with improved player profiles. The results on the two-player game has been generalized to the case of an arbitrary number of players, incorporating additional peak power constraints as well. The uniqueness of the Nash equilibrium is proved analytically. Simulation results show that the proposed method improves the sum rate over 200% relative to the non-cooperative case due to improved frequency reuse.

In this paper, we propose a new multiple relay selection scheme with the availability of outdated channel state information (CSI) for decode and forward (DaF) relay systems, namely the N plus normalized threshold opportunistic relay selection (N+NT-ORS). In particular, we first opportunistically select N best relays out of all relays in the decoding subset with respect to relay-to-destination signal-to-noise ratios (SNRs). Then the ratios of the SNRs on the rest of the relays in the decoding subset to that of the N-th highest SNR are tested against a normalized threshold μ ∈ [0,1] and only those relays passing this test are selected in addition to the N best relays. Through the derivation of the moment generating function (MGF) of SNR, together with the relationship between MGF and outage probability, we obtain a closed-form expression for the outage probability. In addition to analyzing the asymptotic diversity order for N+NTS-ORS, we also outline a distributed N+NT ORS selection protocol without the need of global CSI at each relay. Numerical results confirm the correctness of the derivation and show how N+NT-ORS outperforms its existing counterparts.

This paper studies the optimization problem for joint precoding design in a multi-antenna downlink channel using relaying. We formulate the joint source and relay precoding design by aiming at sum capacity maximization. Since this problem is in general nonconvex, we first convert this problem into standard convex quadratic programs, and then propose an iterative joint precoding optimization algorithm by utilizing efficient quadratic programming approaches. We observe that the iterative method always yields optimal precoding matrices which diagonalize the compound channel of the backward (source-to-relay) and the forward (relay-to-destination) links at high SNR regimes. Motivated by this observation, we further develop an efficient structured precoding design. Simulation results are presented to verify the effectiveness of our proposed precoding schemes.

In this paper, timing synchronization in high-rate ultra-wideband (UWB) block transmission systems is investigated. A new joint timing and channel estimation scheme is proposed for orthogonal frequency division multiplexing (OFDM) and single carrier block transmission with frequency domain equalization (SC-FDE) UWB systems. The scheme is based on a newly designed preamble for both coarse timing and the subsequent channel estimation. Despite of the presence of coarse timing error, the estimated channel impulse response (CIR) is simply the cyclic shifted version of the real CIR, thanks to the unique structure of the preamble. The coarse timing error (CTE) is then determined from the CIR estimation and used to fine tune the timing position and the frequency domain equalization coefficients. The proposed scheme saves preamble overhead by performing joint synchronization and channel estimation, and outperforms existing timing acquisition methods in the literature in dense multipath UWB channels. In addition, the impact of timing error on channel estimation and the performance of SC-FDE UWB systems are analyzed, and the bit-error-rate (BER) degradation with respect to a certain timing error is derived.

Transmitted reference pulse cluster (TRPC) was recently proposed for low data rate ultra-wideband (UWB) communications due to its robust performance, higher data rate, enhanced reliability and lower implementation complexity compared to the conventional transmitted reference technique. In this paper, we study bi-directional cooperative relay strategies for TRPC UWB networks to extend the coverage and improve the network performance. Several novel cooperative strategies have been proposed, based on a newly defined channel quality indictor that can be easily obtained at relays. These relay approaches do not require estimating the UWB channel state information. Simulation results have demonstrated the effectiveness of the proposed cooperation strategies.

Owing to its spectral efficiency, bidirectional relaying is a promising candidate for information exchange in multiple-user cooperative networks. When the network is limited by resource constraints, amplify-and-forward (AaF) relay protocol is often the choice due to its simplicity and ease of use. Power allocation for AaF protocol has being extensively studied in unidirectional relay networks but how it can be implemented in two-way multiple-relay multiple-user networks has yet to be addressed. In this paper, we consider the adaptive power allocation in bidirectional AaF multiple-relay multiple-user networks. We show that when the multiple-user interference can be removed by a robust channel assignment algorithm, power allocation by maximizing the instantaneous sum rate or minimizing the symbol error rate can be suitably casted as a geometric programming (GP) problem. Simulation results show adaptive power allocation by GP outperforms that of equal power allocation scheme particularly when there is a single serving relay, and the gain can be as substantial when there are multiple serving relays.

We consider a MIMO relay downlink system using precoding and limited feedback from two-hop channels. Since the conventional precoding matrices are directly obtained by treating the quantized channel state information (CSI) feedback as the real CSI, we propose an improved relay precoding strategy by taking the effect of channel quantization error into account. The proposed relaying technique is designed based on the minimum mean square error (MMSE) criterion and is robust to the channel uncertainties due to quantized CSI feedback. Numerical results verify the effectiveness of the proposed scheme.

This paper investigates the joint precoding optimization problem for a relay-assisted multi- antenna downlink system. Aiming at multiuser sum capacity maximization, we first propose an iterative optimization algorithm which exploits quadratic programming approaches. We observe that the iterative method always yields the optimized precoding matrices which diagonalize the compound channel of the system at high SNR regimes. Inspired by this observation, we further develop an efficient source and relay precoding strategy by diagonalizing the compound channel of the backward (source-to- relay) and the forward (relay-to-destination) links. Simulation results verify the effectiveness of our proposed precoding schemes.

This paper deals with the interference mitigation problem of the distributed space time block coded (STBC) amplify-and-forward (AF) cooperative orthogonal frequency division multiplexing (OFDM) signal in the presence of carrier frequency offsets (CFO). Multiple CFOs introduce phase drift, inter-carrier interference (ICI) and inter-block interference (IBI) to the received signal. A joint time domain (TD) and frequency domain (FD) method is presented to recover the phase distortion and mitigate the ICI and IBI with low complexity and high performance. The TD compensation proposed in this paper removes the IBI first and then the ICI is mitigated through FD equalization (FDE) methods. For the FDE, the minimum mean square error (MMSE) equalizer has been derived which has a different noise covariance matrix from the conventional MMSE. Sub-block processing is employed to reduce the computational complexity in FD equalization. Furthermore, a two-pilot-block assisted channel estimation method is proposed for AF cooperative OFDM in the presence of CFOs. The bit-error-rate (BER) performance evaluated via computer simulation demonstrates the effectiveness of the proposed method.

We consider a MIMO relay downlink system using beamforming techniques with quantized channel state information (CSI) feedback from two hop channels. With this scheme, each remote user feeds back its quantized CSI to the relay, and the relay sends the quantized beamforming vectors to the base station (BS). An upper bound on the rate loss due to feedback quantization is first characterized. Then, a strategy of scaling the quantization accuracy of both hop links in order to maintain the rate loss within a predetermined gap for growing SNRs is proposed. It is revealed that the numbers of feedback bits of both links should scale linearly with the transmit power at the relay, while the number of feedback bits from the relay to the BS needs to grow with the transmit power at the BS.

This paper describes the implementation detail of an ultra wideband transmitted reference pulse cluster (TRPC) system. The newly proposed TRPC signaling structure consists of multiple pulses with uniform and compact spacing. It overcomes the major hurdle to practical implementation of conventional transmitted reference (TR) systems, that is, the long wideband delay line requirement. In addition, TRPC offers superior error performance and increases the data rate over conventional TR. A modular prototyping platform implemented with discrete commercial off the shelf components and commercial test equipment is built. It adopts binary phase shift keying (BPSK) modulation scheme, employs the TRPC signaling method, and communicates over a wireless link using a direct conversion architecture. The experimental results presented demonstrate that the TRPC system can work stably and robustly, and is able to achieve a transmission rate of 1-10 Mbps in dense multipath environments. The prototype can assist the design and verification of the analog front end and digital baseband models for future commercial integrated UWB TRPC systems.

In this paper, a low-complexity iterative receiver combining joint iterative channel estimation with symbol detection is proposed for coded orthogonal frequency division multiplexing (OFDM) systems in fast fading channels with Doppler frequencies up to 15% of the OFDM symbol rate. The receiver exchanges information between the channel estimator and detector in an iterative fashion to obtain accurate estimates of the channel state information (CSI). The channel is modelled as a weighted sum of fixed basis expansion model (BEM) functions. The BEM channel coefficients are estimated with a Kalman filter. The initial channel estimate is performed from sparse pilot signals. Data is detected and decoded and the channel is estimated again based on the estimated transmitted data. The cycle of data detection, decoding, and channel estimation is repeated until convergence. It is shown that with a pilot to data ratio of 7/144 and with pilots consuming only 1/145 of transmission power, bit error rate performance within 0.1 dB of those achieved with perfect CSI is obtained.

This paper investigates the user selection strategy in multiuser downlinks using zero-forcing beamforming (ZFBF) and finite-rate feedback (FRF). In order to mitigate the interference-limited effect, we propose an efficient user scheduling scheme combined with adaptive transmission mode selection to achieve a better diversity and multiplexing tradeoff in terms of the sum rate performance. In this scheme, each user first evaluates its preferred transmission mode and the corresponding achievable rate according to a derived tight lower bound to the rate. Given such information available through feedback, the base station then determines the global transmission mode of the system and selects users for simultaneous transmissions. Simulation results demonstrate the performance of our proposed scheme.

A recently proposed transmitted reference pulse cluster (TRPC) structure contains compactly spaced reference and data pulses, and enables a low complexity, robust and practical auto-correlation detector to be used at the receiver. Previous research indicated that the integration interval of the auto-correlation detector is critical to the performance of TRPC. Therefore, in this paper, three practical data-aided algorithms are introduced to determine the integration interval of the TRPC structure: the conventional threshold-crossing concept, the new bit error rate (BER) minimization based approach, and the new hybrid scheme that combines threshold-crossing and the BER minimization concepts. The performances of the three schemes are extensively evaluated by simulation. Results show that, the BER minimization based approach and the hybrid scheme demonstrate around 2 dB performance gain over the threshold-crossing scheme in IEEE 802.15.4a channels. Moreover, the hybrid scheme yields close performance to the BER minimization based scheme with much reduced complexity.

One of the most attractive features of ultra-wideband impulse radio is the collection of rich multipath with the transmission of ultra-short pulses. Exploiting the rich multipath diversity with channel estimating Rake receivers enables significant energy capture, higher performance and flexibility than suboptimal receivers. Although data-aided (DA) maximum likelihood (ML) channel estimator shows a promising performance, its implementation is restricted by the Nyquist sampling criterion. The emerging theory of compressed sensing (CS) describes a novel framework to jointly compress and detect a sparse signal with fewer samples than the traditional Nyquist criterion. In this paper, we propose a CS-ML channel estimator which combines the compression framework of CS for sampling rate reduction while retaining the noise statistics formulation of ML to achieve a reliable performance. Simulation assessment indicates that, with far fewer measurements, the performance of our proposed scheme supersedes that of the 4-norm minimization estimator of CS and can be as close as the ML, but with a reduction in complexity.

Theoretical models of ultrawideband (UWB) radio channels indicate that pairs of UWB radio transceivers measure their common radio channel with a high degree of agreement and third parties are not be able to accurately estimate the state of the common channels. These properties allow generation of secret keys to support secure communications from UWB channels measurements. In this paper, the results of UWB propagation studies are presented that validate the required properties to support secret key generation in a typical indoor environment. Key generation algorithms are employed on the measured data and key lengths on the order of thousands of bits are obtained capable of supporting most popular cryptographic systems. The paper also reports measurements of the spatial and temporal correlation of the UWB channel from which the relative privacy of the secret keys can be determined as well as the rate new secret keys may be generated.

In this paper, a new joint timing and channel estimation scheme is proposed for orthogonal frequency division multiplexing and single carrier block transmission ultra- wideband (UWB) systems. In particular, a new preamble pattern is used for both coarse timing and channel estimation. Despite of the presence of coarse timing error, the estimated channel impulse response (CIR) is simply the cyclic shifted version of the real CIR, thanks to the unique structure of the preamble. Then a new method is proposed to search for the first channel tap in the CIR vector, which can be employed to fine tune the timing position and adjust the channel estimation for later data block detection. The proposed scheme has low complexity, saves preamble overhead by performing joint synchronization and channel estimation, and outperforms existing timing acquisition methods in the literature by a large margin in dense multipath UWB channels. Moreover, this paper presents an analysis of the effect of residual timing error on the performance of single carrier systems with frequency domain equalization.

Ultra-wideband (UWB) technology offers promising solution for future indoor high speed low power wireless communications. The development and design of the UWB systems require detailed characterization of UWB indoor channels, and much work has been reported in the literature. However, the temporal variation induced by people's motion in the vicinity of the transceiver has been scarcely investigated. This paper presents the results of extensive measurements and analysis of the temporal variations of UWB indoor radio propagation channel. Impulse based time domain measurements were carried out and the measurement campaign was conducted in diversified environments in a modern office building, consisting of office, hallway and lobby scenarios. Signal strength fluctuation, time correlation coefficient and Doppler spread are derived from the analysis of the measured data. Moreover, the results emphasize the difference of the temporal fluctuation between UWB and narrow band indoor channels.

This paper aims to give an empirical evaluation and analysis on ultra-wideband (UWB) channel properties, which differ quite significantly from their narrowband counterpart. Time domain measurements are performed to investigate the property of channel reciprocity, spatial correlation and body shadow effect. First of all, UWB reciprocity is observed under both baseband and radio frequency (RF) transmission, and it is observed to be distance independent and frequency independent. In addition, the spatial correlation fluctuates with distance in a two dimensional grid, and an investigation of multiple antenna spacing is provided. Finally, body shadow effect is investigated by studying the signal strength affected by placement of human body obstruction on the transmission path.

This paper examines a WiMedia UWB product by performing comprehensive throughput measurements and a path loss and link budget analysis based on the measured data in office and residential environments. The UWB product conforms to WiMedia's multi-band orthogonal frequency division multiplexing specification. The link budget analysis results together with detailed throughput versus range measurements demonstrate the impressive performance of the WiMedia UWB module for high speed data transfer under very low power constraint, e.g., 0 dB fade margin and capable of supporting up to 324 Mb/s in iPERF.

In this paper, we study the asymptotic performance of absolute-threshold and normalized-threshold- based generalized selection combining (AT-GSC and NT-GSC) schemes over generalized fading channels for high average signal-to-noise ratio (ASNR). By evaluating the asymptotic moment generating function (MGF) of the threshold-based GSC (T-GSC) output SNRs, we derive the diversity and combining gains for AT- and NT-GSCs with a large class of modulation formats and versatile fading conditions, including different types of fading channels and non-identical SNR statistics across diversity branches. Our analytical results reveal that the diversity gains of AT- and NT-GSC are equivalent to that of maximum ratio combining (MRC), and the differences in the combining gains for different threshold values, and modulation and diversity formats, are derived using the concept of the modulation factor.

A recently proposed transmitted reference pulse cluster (TRPC) structure contains compactly spaced reference and data pulses, and enables a low complexity, robust and practical auto-correlation detector to be used at the receiver. TRPC has been shown to outperform the conventional transmitted reference and non-coherent pulse position modulation systems in ultra-wideband channels. Previous research indicated that the integration interval of the auto-correlation detector is critical to the performance of TRPC. In this paper, practical data-aided algorithms are introduced to determine the integration interval of the TRPC structure based on minimizing the system bit error rate. The proposed scheme is compared to the traditional threshold crossing method and demonstrates around 2 dB performance gain in IEEE 802.15.4a channels. A simplified version of the scheme valid for low signal to noise ratios is also presented. The proposed integration interval determination method does not require Nyquist rate sampling or analog averaging with symbol long delay lines, and is therefore suitable to practical implementation.

Non-coherent detection and auto-correlation detection are promising techniques for low complexity, low cost and low data rate ultra-wideband communication applications. For both schemes, the integration region of a receiver integrator significantly affects the bit error rate (BER) performance. In this paper, a method of synchronization and estimating the optimal integration region, i.e., the initial point and the length of the integration, is presented. Following a theoretical BER analysis, a data-aided estimation method using the idea of inter-symbol correlation is proposed. It is shown that using noise corrupted received signals, the proposed method is not only practically applicable, but also enhances the performance compared to non-optimal timing methods.

Ultra-wideband (UWB) signals can be used for accurate time of arrival (TOA) based ranging because of their high time resolution. In this paper, a novel data-aided TOA estimation method is presented using dual pulse (DP) signal structure. It employs received signal autocorrelation and threshold crossing to detect the direct path. The effects of different threshold values and training sequence lengths on the estimation accuracy of the proposed method are studied. The performance improvement of this approach over the conventional energy detection based method is also demonstrated via simulation.

A new form of transmitted reference technique is proposed in this paper, where compactly spaced or even multiple contiguous reference and data pulses are used for transmission. This structure enables a simple, robust and practical autocorrelation detector to be implemented in the receiver. It is also compatible with the signal format proposed within IEEE 802.15.4a working group for coherent and non-coherent systems. The performance of the proposed receiver and a simple noncoherent energy detector are analyzed and compared. Simulation results show that this new transmitted reference system outperforms the non-coherent system by about 1.3-1.9 dB for 802.15.4a channel model 1 and 1.3-2.3 dB for channel model 8, while offering similar implementation complexity compared to that of the non-coherent system.

In the UWB transmitted reference (TR) schemes, the integration region of a receiver integrator significantly affects the bit error rate (BER) performance. In this paper, a method of synchronizing and estimating the optimal integration region, i.e., the initial point and the length of the integration, is presented. Following a theoretical analysis, a data-aided estimation method using the idea of intersymbol correlation is proposed. It is shown that using the noise corrupted received signals, the proposed method is not only practically applicable, but also enhances the performance compared to non-optimal timing methods.

In this paper, we investigate several efficient interpolation techniques for pilot symbol assisted channel estimation in OFDM. The interpolation methods studied include two dimensional (2-D) separable lowpass sine interpolator with Kaiser window, 2-D separable Deslauriers-Dubuc (DD) interpolation and 2-D discrete Fourier transform (DFT) based lowpass interpolation. The performances of these interpolators are compared with those of the well known minimum mean-square error (MMSE) 2-D separable Wiener filter and the perfect channel state information. It is shown that the Kaiser window based interpolator and DD interpolation are simple, robust, and outperform the 2-D DFT based lowpass interpolation as well as several existing interpolation methods proposed in the literature. These two schemes are suitable candidates for use in 1-D and 2-D channel estimation

This paper investigates spectrum shaping in ultra-wideband (UWB) communications in order to introduce spectral nulls to limit interference with narrowband signals. Each transmitted symbol is represented by a "coded Gaussian monocycle pulse" in which Gaussian monocycles are weighted, delayed and summed in accordance with a designed codeword. The use of the Gaussian monocycle ensures that the UWB spectrum mask established by the Federal Communications Commission (FCC) is met, and the codeword is designed to generate a spectral null at the frequency or frequencies being used by existing narrowband devices. Signals obtained with different spectrum shapings (e.g., Butterworth, Chebyshev, elliptical) and by introducing nulls at multiple interference frequency bands are discussed. This approach can be used in various systems; as one application, we simulate the performance of a coded monocycle UWB system with a spectral null in the presence of narrowband interference (NBI) using single carrier block transmission with frequency domain equalization (SC-FDE), and compare its performance with that of an uncoded SC-FDE UWB system using a single Gaussian monocycle. Our results show that NBI can be effectively suppressed by transmitting and matched filtering the pulse with a spectral null at the interference frequency, therefore improving the robustness of UWB systems to NBI

We investigate in this paper the effect of carrier frequency offset (CFO) and sampling timing offset (STO) on the performance of single carrier block transmission with frequency domain equalization (SC-FDE) over ultra-wideband (UWB) channels. Signal-to-interference-plus-noise ratio (SINR) of SC-FDE UWB in the presence of CFO is analyzed and compared with that of OFDM, where OFDM is shown to be more sensitive to CFO. We also study the effect of STO on the performance of SC-FDE. Two forms of STO are considered, i.e., a shifted sampling timing instant other than the optimal timing point and a distorted sampling rate other than the symbol rate. Our results show that the performance of SC-FDE is rather channel dependent when sampling at a non-optimal time instant within one symbol duration, where the energy of the sampled equivalent channel at the sampling point determines its BER performance. Moreover, an SC-FDE system is fairly sensitive to a distorted sampling rate at the receiver, where severe performance degradation can occur when the received signal is sampled at a sampling rate rather than symbol rate.

This paper investigates spectrum shaping in ultrawideband (UWB) communications in order to introduce spectral nulls to limit interference with narrowband signals. Each transmitted symbol is represented by a monocycle "coded" Gaussian pulse, where use of the monocycle Gaussian pulse ensures that the UWB spectrum mask established by the Federal Communications Commission (FCC) is met and where the codeword is designed to generate a spectral null at the frequency or frequencies being used by existing narrowband devices. Signals obtained with different spectrum shapings (e.g., Butterworth, Chebyshev, elliptical) and by introducing nulls at multiple interference frequency bands are discussed. The performance of a monocycle coded UWB system with a spectral null in the presence of narroband interference (NBI) using single carrier block transmission with frequency domain equalization (SC-FDE) is simulated and compared with that of an uncoded SC-FDE UWB system using a single Gaussian monocycle. Our results show that NBI can be effectively suppressed by transmitting and matched filtering the pulse with a spectral null at the interference frequency, therefore improving the robustness of SC-FDE UWB to NBI.

We propose a time-division multiple-access (TDMA) scheme for the binary phase-shift keying (BPSK) modulated single carrier block transmission with frequency domain equalization (SC-FDE) over ultra-wideband (UWB) channels. The transmitter and receiver matrices for the proposed TDMA SC-FDE system are derived to achieve the multiple-access interference (MAI) free and interblock-interference (IBI) free transmission without the insertion of cyclic prefix (CP) between blocks, avoiding long CP and large fast Fourier transform (FFT) size in high-speed UWB communications. The performance of the proposed TDMA SC-FDE system over UWB channels is investigated and compared with that of the block spread code-division multiple-access (CDMA) scheme. The impact of oversampling diversity and imperfect channel estimation on the performance of the proposed system are also investigated. Results show that the proposed TDMA scheme can effectively eliminate the error floor in CDMA due to insufficient CP, and it is more efficient to accommodate larger number of users than CDMA in high data rate transmission.

This letter proposes cyclic prefixed single carrier transmission with frequency domain equalization (SC-FDE) as an alternative physical layer solution for UWB communications. The performance of SC-FDE over IEEE 802.15.3a UWB channel models is analyzed, simulated and compared with that of impulse based single carrier UWB (SC-UWB) and multicarrier UWB employing orthogonal frequency division multiplexing (OFDM-UWB). The impact of channel coding on the performance of OFDM and SC-FDE in UWB is also studied. Our results demonstrate performance advantage of the SC-FDE scheme, especially when implementation issues such as low complexity and low power consumption for UWB are taken into consideration. The performance of SC-FDE with diversity combining using oversampling is also investigated

In this paper, we introduce a novel performance analysis approach based on partitioning the probability space. This new performance analysis approach enables a unified analysis of normalized threshold generalized selection combining (NT-GSC) over generalized fading channels. To further improve the robustness of the NT-GSC combiner, we propose and analyze a generalized NT-GSC scheme referred to as N-branch plus normalized threshold generalized selection combining (TV+NT-GSC). Performance measures are obtained through the derivation of the moment generating function (MGF) of the diversity combiner output signal-to-noise ratio (SNR). Implementation complexity of NT-GSC and TV+NT-GSC are investigated, and the mean and variance of the number of combined branches are derived in a compact form for general fading channels.

This paper investigates the design of practical sine interpolation filters in pilot symbol assisted modulation (PSAM) systems. By closely examining the error mechanism in PSAM channel estimation, we show that the error floor phenomenon is caused by the non-ideal characteristic of the interpolation filter. Based on the use of adjustable window functions, we present a set of design guidelines to determine the shape of window functions, the window/filter length and the pilot insertion rate. The design choices essentially reflect the trade-offs between error performance, implementation complexity and transmission rate.

In this paper, the application of low-density parity-check convolutional codes (LDPC-CCs) to packet based communication systems is studied. By presenting analysis of encoder and decoder design as well as simulation results for such systems, we show that LDPC-CCs are more suited to packet based applications than LDPC block codes (LDPC-BCs). This is due to their ability to operate on arbitrary lengths of data, lower encoder complexity and the performance gain of presetting and termination. Moreover, in this paper, we propose an algorithm for terminating the LDPC-CC encoder from any state to the all-zero state.

Recently, single carrier block transmission with frequency domain equalization (SC-FDE) has been shown to be a promising candidate for ultra-wideband (UWB) communications. In this paper, we address the channel estimation problem for SC-FDE transmission over UWB channels. A mean square error (MSE) lower bound for the frequency domain LMMSE channel estimator is derived and the optimal pilot sequence that achieves this lower bound is obtained. Further simplification leads to a frequency domain channel estimator with reduced computational complexity. The performance of the simplified estimator for SC-FDE over UWB channels is evaluated and compared with that of perfect channel state information. The effects of non-optimal and optimal pilot symbols are also investigated. Our results show that the proposed frequency domain channel estimator performs well over UWB channels with only small performance degradation compared to the perfect channel estimation

We propose a time division multiple access (TDMA) scheme for the BPSK modulated single carrier block transmission with frequency domain equalization (SC-FDE) over ultra-wideband (UWB) communications. The transmitter and receiver matrices for the proposed TDMA SC-FDE system are derived to achieve the multiple access interference (MAI) free and interblock-interference (IBI) free transmission without the insertion of cyclic prefix (CP) between blocks, circumventing the need for long CP and large FFT size in high speed UWB communications. The performance of the proposed TDMA SC-FDE system over UWB channels is investigated and compared with that of the block spread code division multiple access (CDMA) scheme. The effects of oversampling diversity and imperfect channel estimation are also investigated. Results show that the proposed TDMA scheme can effectively eliminate the error floor in CDMA due to insufficient CP, and it is more efficient to accommodate larger number of users than CDMA in high data rate transmission

A new UWB signaling technique based on dual pulse transmission is presented in this paper. The proposed technique is simple, robust, and based on an autocorrelation type of receiver structure. Several detection schemes with different implementation complexity are presented and their performances are studied by Monte-Carlo simulations. Comparison of the proposed new designs to the transmitted reference system is also carried out in the paper.

This paper investigates the performance of cyclic prefixed single carrier with frequency domain equalization (SC-FDE) transmission over the ultra-wideband (UWB) propagation environment. The performance of SC-FDE over IEEE 802.153a UWB channel models is analyzed, simulated and compared with that of impulse based single carrier UWB (SC-UWB) and multicarrier UWB (MC-UWB) employing orthogonal frequency-division-multiplexing (OFDM). The impact of channel coding with different code rates on the performance of OFDM and SC-FDE in UWB is also studied. Our results demonstrate conclusive performance advantage of the SC-FDE scheme, especially when implementation issues such as low complexity and low power consumption for UWB are taken into account.

In this paper, we propose and analyze a new generalized selection combining (GSC) scheme referred to as N-branch plus normalized threshold generalized selection combining (N+NT-GSC). Performance measures are obtained through the derivation of the moment generating function (MGF) of the diversity combiner output signal-to-noise ratio (SNR) for generalized fading channels. Implementation complexity of N+NT-GSC is investigated, and the mean and variance of the number of combined branches are derived in compact forms. The new N+NT-GSC is shown to bridge the characteristics of normalized threshold generalized selection combining (NT-GSC) and the conventional GSC, and exhibit better robustness than previously proposed NT-GSC over branch imbalance and fading distributions.

The performance of a joint Rake and minimum mean square error (MMSE) equalizer receiver for high data rate ultra-wideband communications is studied in this paper. The proposed receiver combats intersymbol interference by taking advantage of the Rake and equalizer structure. The receiver performance is investigated using a semi-analytical approach and Monte-Carlo simulations. The effects of the number of Rake fingers and equalizer taps on the error performance are examined. For an MMSE equalizer at low to medium SNR, the number of Rake fingers is the dominant factor to improve system performance. while at high SNR the number of equalizer taps plays a more significant role in reducing error rates. The effect of channel estimation error on the performance of the Rake-MMSE-equalizer is also studied through simulations in this paper.

Analytical probability of error expressions are presented in this paper for coherent orthogonal, biorthogonal and transorthogonal signaling in slow Nakagami fading channels with diversity reception. These new probability of error expressions are exact, numerically efficient, and general for arbitrary signal dimension. The numerical results obtained from the newly derived probability of error formulae can guide system engineers in determining the appropriate dimensionality of the orthogonal and biorthogonal signals. They can also be useful for authoritatively deciding the suitable number of diversity branches used at the receiver to meet the design requirements in a wireless fading environment.

Analytical probability of error expressions are presented in this paper for orthogonal, biorthogonal, and transorthogonal signaling in slow Nakagami fading channels with diversity reception. These new probability of error expressions are exact, numerically efficient, and general for arbitrary signal dimension. The numerical results obtained will guide system engineers in determining the appropriate dimensionality of the orthogonal, biorthogonal, and transorthogonal signals. They will also be useful for deciding the suitable number of diversity branches used at the receiver to meet the design requirements in wireless fading environments.

A general method is presented for the computation of the exact bit error probability for arbitrary two-dimensional (2D) signaling with polygonal decision regions in various channel environments. This new approach is general in the sense that it applies to any coherent 2D constellation, any bit-to-symbol mapping, and various environments such as additive white Gaussian noise (AWGN) channels and slow fading channels with and without diversity reception and channel estimation error. The considered performance measures include the exact bit error probability, the symbol error probability, the mutual information and the error probabilities of individual bits in a constellation. The proposed new approach is exact and easy to evaluate, thus avoiding the need for computer simulation.

The paper presents a general analysis on the performance of selection combining (SC) systems in Rayleigh fading channels with imperfect channel estimation (ICE). The channel estimate and the actual fading are modeled as complex joint Gaussian random variables. Simple single integral formulas with finite integration limits are derived for the symbol error probability (SER) of an arbitrary two-dimensional (2D) modulation format, and a closed-form expression is obtained for the SER of M/sub s/-PAM. These error probability expressions are then applied to three types of channel estimation errors possibly encountered in practical systems to study their impact on the performance of selection diversity. Other applications of this general analysis include semi-analytical simulation of practical communication systems.

This paper investigates the design of practical sinc interpolation filters in pilot symbol assisted modulation (PSAM) systems. By closely examining the error mechanism in PSAM channel estimations, it is shown that the error floor phenomenon is caused by the non-ideal characteristic of the interpolation filter. We present a set of design guidelines to determine the shape of window functions, the window/filter length and the pilot insertion rate. The design choices essentially reflect the trade-offs between error performance, implementation complexity and transmission rate.

The analytical framework reported in X. Dong et al. (May 2003) for calculating the symbol error rate (SER) of two-dimensional (2-D) signaling in Rayleigh fading with channel estimation errors is further developed to address the more general case of frequency-flat Ricean fading. We show that in the presence of channel estimation errors, the SER of arbitrary 2-D signaling with polygonal decision regions in Ricean fading can be expressed as a two-fold proper integral with finite integration limits, which is suitable for numerical evaluation. Moreover, this new analysis is general in the sense that it is applicable to any channel estimation scheme where the estimated and the actual channel gains are jointly complex-Gaussian. The effect of static channel estimation errors and dynamic channel estimation errors introduced by pilot symbol assisted modulation (PSAM) and minimum mean square error (MMSE) channel estimations are studied using the newly derived SER formula. The effect of Doppler frequency shift in the line-of-sight (LOS) component of the channel on the error performance is investigated in our analysis. The analytical and numerical results presented in this work provide a useful tool on choosing suitable signaling formats and optimizing parameters in the communication system design.

A general analytical framework for evaluating the performance of practical coherent two-dimensional (2-D) signaling in frequency flat Rayleigh fading with channel estimation is proposed in this paper. A new and simple analytical expression for the symbol error rate (SER) of an arbitrary 2-D constellation in Rayleigh fading in the presence of channel estimation errors is presented. This framework is applicable to many current channel estimation methods such as pilot symbol aided modulation and minimum mean square error estimation where the fading estimate is a complex Gaussian variable correlated with the channel fading. The sensitivity of various 2-D signaling formats to static and dynamic channel amplitude and phase estimation errors in Rayleigh fading can be easily studied using the derived formula. The new exact SER expression makes it possible to optimize constellation parameters and various parameters associated with channel estimation schemes. It also provides insights into choosing an appropriate signaling format for a fading environment with practical channel estimation methods used at the receiver.

New exact expressions for the symbol-error rate and bit-error rate of coherent 3-ary and 4-ary orthogonal and transorthogonal signaling in slowly fading Rayleigh channels are derived. New exact error probability expressions for coherent 6-ary and 8-ary biorthogonal signaling in slow Rayleigh fading are also presented. The use of these exact expressions as accurate approximations for the error rates of M-ary orthogonal, biorthogonal, and transorthogonal signaling with arbitrary M is illustrated.

A new exact method for computing the average symbol error probability of two-dimensional M-ary signaling in slow fading is presented. The method is generally applicable to polygonal decision regions. The exact average symbol error rate of coherent 16-star-QAM is obtained and compared to that of 16-rectangular-QAM. New results for optimum ring ratios of 16-star-QAM in additive white Gaussian noise (AWGN) and in slow fading are also given.

The performance of various coherent 8-ary and 16-ary modulations in additive white Gaussian noise (AWGN) and slowly fading channels are analyzed. New expressions for the exact symbol error rates (SER) in fading with diversity combining are derived for any two-dimensional signaling format having polygonal decision boundaries. Maximal ratio combining, equal gain combining, and selection combining are considered. The SER formulas obtained make it possible for the first time to optimize parameters of various constellations precisely and to determine,which constellation has the lowest probability of error. For example, a star constellation such as that specified in the CCITT V.29 standard can be improved by adjusting the amplitude ratios of the points in the constellation to save about 0.63 dB power in AWGN without sacrificing the phase error tolerance, while maintaining the same error rate. The sensitivity of each constellation to phase error is presented and comparisons are made. Six 8-ary signal sets and 11 16-ary signal sets are examined using the new symbol error probability formulas to determine best signal sets for fading channels.

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.