This paper investigates movable-antenna (MA) enabled intelligent reflecting surface (IRS)-aided integrated sensing and communication (ISAC) systems, where an MA-enabled base station (BS) serves multiple downlink communication users (CUs) and performs direction-of-arrival (DOA) estimation for a target. The goal is to improve communication performance while satisfying a Cram´er–Rao bound (CRB) requirement for sensing. To balance performance and computational complexity, two MA control schemes including element-wise and array-wise control schemes are considered, allowing antenna elements to adjust their positions individually or in groups as arrays. Two communication rate performance metrics including the sum-rate and minimum-rate are considered to evaluate the throughput and fairness of multi-user communications. To solve the non-convex optimization problems, we develop a product Riemannian manifold optimization (PRMO) method that constructs a product Riemannian manifold space (PRMS) and integrates a penalty method with a Riemannian Broyden–Fletcher–Goldfarb–Shanno (RBFGS) algorithm. Simulation results validate the effectiveness of the proposed PRMO method and show that MA offers advantages over conventional fixed-position antenna (FPA) in IRS-aided ISAC systems. Moreover, simulation results show that while the element-wise control scheme yields the best overall performance, the array-wise control reduces the execution time by over 60% while sacrificing no more than 5% of the achievable communication rate compared with the element-wise control.

Intelligent reflecting surface (IRS) and movable antenna (MA) technologies have been proposed to enhance wireless communications by creating favorable channel conditions. This paper investigates the joint beamforming and antenna position optimization for MA-enabled IRS (MA-IRS)-aided multi-user multiple-input single-output (MU-MISO) communication systems, where the MA-IRS is deployed to aid the communication between the MA-enabled base station (BS) and user equipment (UE). In contrast to conventional fixed position antenna (FPA)-enabled IRS (FPA-IRS), the positions of the reflecting elements of the MA-IRS can be controlled to enhances the wireless channel. To verify the system’s effectiveness and optimize its performance, we formulate a sum-rate maximization problem with a minimum rate threshold constraint for the MU-MISO communication. To tackle the non-convex problem, a product Riemannian manifold optimization (PRMO) method is proposed for the joint optimization of the beamforming and MA positions. Specifically, a product Riemannian manifold space (PRMS) is constructed and the corresponding Riemannian gradient is derived for updating the variables, and the Riemannian exact penalty (REP) method and a Riemannian Broyden-Fletcher-Goldfarb-Shanno (RBFGS) algorithm is exploited to obtain a feasible solution over the PRMS. Simulation results demonstrate that compared with the conventional FPA-IRS-aided communications, the reflecting elements of the MA-IRS can move to the positions with higher channel gain, thus enhancing the system performance. Furthermore, it is shown that optimizing the positions of the reflecting elements brings higher performance gain than controlling the phase shifts of the IRS, and integrating MA with IRS leads to higher performance gains compared to integrating MA with BS.

Driven by intelligent reflecting surface (IRS) and movable antenna (MA) technologies, movable IRS (MIRS) has been proposed to improve the adaptability and performance of conventional IRS, enabling flexible adjustment of the IRS reflecting element positions. This paper investigates MIRS-aided integrated sensing and communication (ISAC) systems. The objective is to minimize the power required for satisfying the quality-of-service (QoS) of sensing and communication by jointly optimizing the MIRS element positions, IRS reflection coefficients, transmit beamforming, and receive filters. To balance the performance-cost trade-off, we proposed two MIRS schemes: element-wise control and array-wise control, where the positions of individual reflecting elements and arrays consisting of multiple elements are controllable, respectively. To address the joint beamforming and position optimization, a product Riemannian manifold optimization (PRMO) method is proposed, where the variables are updated over a constructed product Riemannian manifold space (PRMS) in parallel via penalty-based transformation and Riemannian Broyden–Fletcher–Goldfarb–Shanno (RBFGS) algorithm. Simulation results demonstrate that the proposed MIRS outperforms conventional IRS in power minimization with both element-wise control and array-wise control. Specifically, with different system parameters, the minimum power is achieved by the MIRS with the element-wise control scheme, while suboptimal solution and higher computational efficiency are achieved by the MIRS with array-wise control scheme.

The rapid evolution of reconfigurable intelligent surfaces (RISs) has opened new frontiers in channel impairment mitigation, particularly through passive beamforming. However, when integrated with waveforms under doubly selective channels, a fundamental timescale mismatch exists: the existing RIS designs typically employ a single static phase configuration per frame due to hardware constraints, whereas the channel is time-varying. To address this issue, we propose a novel RIS-aided orthogonal time frequency space (OTFS) system integrated with index modulation (IM). IM serves as a generalized framework encompassing conventional modulation, enhancing the spectral efficiency (SE) and transmission flexibility. By analyzing the structure and energy distribution of time-varying channels in the delay-Doppler (DD) domain, we develop a diagonal phase alignment (DPA) strategy that aligns the RIS-reflected paths with the direct path, maximizing the achievable rate with negligible computational overhead. Unlike existing works, we explicitly consider the impact of imperfect biorthogonality in rectangular pulse-shaping waveforms, which alters the structure of the equivalent channel matrix. This paper provides detailed mathematical system models and RIS deployment scenarios. Furthermore, the closed-form upper bound of bit error rate (BER) is derived for Rician fading channels. Simulation results validate the theoretical analysis and demonstrate promising performance in terms of the achievable rate and BER.

Collision prediction is crucial for safety in Vehicle-to-Everything (V2X) networks, essential for smart cities and intelligent transportation. Traditional methods struggle with complexity, while learning-based approaches face challenges in feature extraction and prediction accuracy. To address this, we propose attentive TabNet for collision prediction in V2X networks. Our model utilizes attention mechanisms in deep neural networks to focus on key spatial and temporal features, enhancing prediction reliability. We also apply data preprocessing to handle imbalances. Experimental evaluations using real-world V2X data show that our method outperforms random forest and neural network-based algorithms in accuracy and efficiency. Both simulations and real-world tests confirm its effectiveness. By improving collision prediction, our approach enhances road safety, advancing intelligent transportation and smart city initiatives.

Due to the increase of signal bandwidth, automotive radar can receive multiple scatting centers from the target of interest. This is typically described by an extended target model. However, existing methods for extended target detection and tracking often exhibit subpar performance because they struggle to adapt to the hybrid-scale and time-varying texture feature exhibited by moving traffic participants. Therefore, this work presents a unified framework hybrid-scale spatio-temporal transformer for joint detection and tracking of hybrid-scale extended targets. It consists of three progressive stages: hybrid-scale embedding network, spatio-temporal transformer, and Wasserstein loss. The hybrid-scale embedding network extracts the features of hybrid-scale targets by parallel multiple convolution kernels of different scales. Then, the spatio-temporal transformer locates targets by integrating these spatial-temporal features across the time. It can allow the target’s hybrid-scale and time-varying texture feature changes incurred through the movement, while eliminating the need for cross frame target association, thus achieving robust detection and tracking. The Wasserstein loss metric is designed to assist the model in optimizing hybrid-scale target location proficiency, especially for small targets. With intensive experiments on simulated datasets and public real datasets, such as RAMP-CNN and RADDet, the proposed model achieves better detection and tracking performance than existing methods with different noise added, and shows strong robustness in various traffic scenarios.

Radio frequency interference (RFI) is an important factor affecting microwave remote sensing observations, causing random degradation of synthetic aperture radar (SAR) images. Due to the huge amount of raw echo and single-look complex (SLC) data, there are some SAR interpretation scenarios when only amplitude images can be obtained, and traditional signal transformation and matrix operations can hardly meet the suppression requirements in the absence of phase information at this time. Although deep learning algorithms have made some progresses on this issue, they still suffer from the following limitations: (i) There are few models dedicated to SAR RFI in the image domain; (ii) The network structure is relatively complex due to not fully exploit the physical characteristics of SAR and RFI. To this end, we propose an end-to-end suppression network (PMNet), which includes a novel explainable feature decomposition module (FDM) based on the idea of non-negative matrix factorization and a composite loss function to achieve dynamic separation of foreground and background features of supervised RFI-contaminated images. The ablation experiment proves that compared with the baseline algorithm, the visual similarity of the proposed PMNet on the test set can be improved by up to 14.15%. The suppression result on Sentinel-1 and Gaofen-3 real data also verifies the effectiveness of the PMNet in different SAR platforms.

Polarization adds an additional dimension to the radar signals, contributing to waveform diversity. Codesign of unimodular waveforms and filters with polarimetric power allocation for maximizing the signal-to-interference-plus-noise ratio (SINR) plays a key role in the polarimetric radar system. The problem is challenging to solve due to the nonconvex nature of the objective function and constraints, coupled with the interdependence of multiple variables. Existing methods mainly solve this problem by fixing the power allocation or relaxing the objective function and obtaining the receive filters with matrix inversion. We directly address this problem without matrix inversion by using the proposed adaptive unified manifold optimization (AUMO) framework. Specifically, a unified manifold space (UMS) is constructed to satisfy the constraints of unimodular waveform, filters, and power, transforming the problem to an unconstrained optimization problem over the manifold. To solve this problem, a parallel conjugate gradient (PCG) algorithm is derived. This algorithm can adaptively change the step size by exploring the local features of the manifold space. The experimental results based on the measured data show that the proposed method outperforms existing methods in terms of SINR gain and execution time.

This paper presents a method for the joint detection and tracking of weak targets in automotive radars using the multi-frame track-before-detect (MF-TBD) procedure. Generally, target tracking in automotive radars is challenging due to radar field of view (FOV) misalignment, nonlinear coordinate conversion, and self-positioning errors of the ego-vehicle, which are caused by platform motion. These issues significantly hinder the implementation of MF-TBD in automotive radars. To address these challenges, a new MF-TBD detection architecture is first proposed. It can adaptively adjust the detection threshold value based on the existence of moving targets within the radar FOV. Since the implementation of MF-TBD necessitates the inclusion of position, velocity, and yaw angle information of the ego-vehicle, each with varying degrees of measurement error, we further propose a multi-frame energy integration strategy for moving-platform radar and accurately derive the target energy integration path functions. The self-positioning errors of the ego-vehicle, which are usually not considered in some previous target tracking approaches, are well addressed. Numerical simulations and experimental results with real radar data demonstrate large detection and tracking gains over standard automotive radar processing in weak target environments.

Adaptive filtering faces significant challenges in handling complex non-Gaussian noise, while graph signal processing (GSP) excels at processing data with intricate structures. This brief introduces a novel method for solving non-Gaussian noise from the perspective of the graph domain for the first time. Specifically, we develop an online time-varying graph model based on the filter error signal and propose a corresponding graph topology transformation strategy. Utilizing a graph smoothness measure, we introduce a new adaptive filtering cost function, in which the graph Laplacian matrix plays a direct role in the filter update process. Subsequently, we derive the graph smoothness recursive adaptive filtering (GS-RAF) algorithm, rigorously analyze its theoretical performance, and validate its efficacy through simulations and echo cancellation experiments. The corresponding MATLAB (MathWorks, USA) codes of the simulations are publicly available at: https://github.com/smartXiaoz/GS-RAF.git.

In this paper, we focus on the joint beamforming for intelligent reflecting surface (IRS) aided integrated sensing and communication (ISAC) systems, where a multi-antenna base station (BS) performs multi-user multi-input single-output (MU-MISO) communication and radar sensing simultaneously. Specifically, the direction-of-arrival (DoA) estimation is considered as the task of radar sensing, and we aim to optimize the MU-MISO communication while enhancing the estimation accuracy by ensuring a Cramér-Rao bound (CRB) lower bound. First, for the CRB-constrained sum rate maximization problem, we propose a product Riemannian manifold optimization (PRMO) framework to solve the problems without relaxing the objective functions. Specifically, a product Riemannian manifold space (PRMS) is constructed to satisfy the constraints of the precoding matrix and IRS phase shifts, and the constraint of the CRB threshold is tackled by a Riemannian exact penalty (REP) method. A parallel Riemannian Broyden-Fletcher–Goldfarb-Shanno (P-RBFGS) algorithm is derived to update the parameters over the PRMS. Then, considering the fairness of the MU-MISO communication, the PRMO is further extended to tackle the CRB-constrained max-min optimization by maximizing the minimum rate among all users. Simulation results demonstrate that with the same CRB constraint, the PRMO outperforms the existing method in sum rate maximization with lower computational complexity, and the extended PRMO enables the users to obtain approximately equal rates, thus guaranteeing the fairness of the system.

Video synthetic aperture radar (SAR) has attracted increasing attention in recent years due to its ability to provide continuous images for the scenes of interest. However, practical applications of video SAR are limited by the large amount of data and computational costs involved in imaging. In this paper, we propose a deep unfolding network for reconstructing SAR videos from undersampled echo data. Firstly, we introduce a low-rank representation operator to perform low-rank representation on the video SAR tensor. Then the problem of reconstructing video SAR is modeled as a regularization problem based on low-rank representation and solved by the alternating direction method of multipliers (ADMM) algorithm iteratively. Finally, we unfold the iterative solution into a deep neural network to learn the network parameters and low-rank representation operator from the data. Simulation experiments validate the effectiveness of the proposed method.

In this paper, we propose a deep learning (DL) based receiver named comm-transformer network (Comm-Trans Net), which is robust for different sub-types of tapped delay line (TDL) channels. The novel Comm-Trans Net considers the attention mechanism to compensate for the multi-path fading effect for different orthogonal frequency-division multiplexing (OFDM) subcarriers. We propose a novel positional encoding method for each OFDM subcarrier, which uses the attention mechanism to offset the deep fading effect. In particular, our proposed Comm-Trans Net serves as an integrated DL-based receiver for unknown channel conditions. Our results show that the proposed Comm-Trans Net can outperform the bit-error rate (BER) performance compared to minimum mean-square error (MMSE) channel estimation with generalized approximate message passing (GAMP) receiver, and also outperforms the state-of-the-art DL-based receivers. Moreover, our proposed Comm-Trans Net is robust for multiple communication scenarios ranging from the TDL-A channel to the TDL-E channel with different levels of non-line-of-sight (NLoS) and line-of-sight (LoS) components. Also, the computational complexity of the proposed Comm-Trans Net is studied, which shows that the attention mechanism for channel positional encoding is a cost-effective solution to improve the quality of service.

High-resolution synthetic aperture radar (HR-SAR) is extensively used in ground remote sensing applications, including disaster monitoring and resource crop assessment. This is attributed to its exceptional high-resolution imaging capabilities. Microwave photonics technology plays a crucial role in enhancing the performance of SAR systems. It enables the direct emission of ultra-wideband signals across multiple frequency bands. However, this advancement also makes microwave photonic synthetic aperture radar (MWP-SAR) susceptible to complex and diverse electromagnetic interference. Particularly, it is vulnerable to radio frequency interference (RFI), and this interference seriously affects the high-resolution imaging results. In order to solve these problems, an MWP-SAR imaging algorithm based on depth spectral sensing and spectral reconstruction that is suitable for complex electromagnetic environments is proposed. Simultaneously, a sensing-removing-recovering (SRR) anti-interference imaging framework is established. To address the high-precision detection of various unknown interferences in MWP-SAR echoes, a deep learning network is constructed. This network is based on spectrum sensing theory and achieves an interference detection probability greater than 98% in various interference scenarios. Subsequently, targeting the continuous spectrum loss in the MWP-SAR signal after interference removal, a signal reconstruction algorithm is proposed. This algorithm employs Toeplitz transformation for signal loss scenarios, facilitating the recovery of signals with extensive spectrum loss post-interference removal. The factor group sparse regularization (FGSR) algorithm is used to quickly solve the signal recovery problem. Through simulation and measured data processing, the superiority of the proposed algorithm over existing interference suppression imaging algorithms is demonstrated.

In this article, we develop a multiframe detection architecture relying on the generalized likelihood ratio test (GLRT) to address complicated multitarget detection and tracking in radar systems. The commonly used and unrealistic assumptions made in the previous works, where targets are sufficiently far apart from each other and do not occupy the same measurement cell (only for high-resolution radars), can be relaxed. Specifically, at the design stage, we take full account of the energy integration of real targets over multiframe measurements and the accurate data association of multitarget tracks for arbitrarily located targets. To solve the above challenges, a new detection statistic including the amplitude likelihood and the transition cost of a search path is derived. Then, we come up with two detection schemes for both known and unknown number of targets consisting of the log-likelihood ratio, an offsetting term about the transition cost and a penalty term accounting for the unknown number of targets. Finally, a fast implementation for the above detectors is investigated to trade detection and tracking performance for a lower computational complexity. Interestingly, the proposed architectures can not only improve detection performance for multiple dim targets through noncoherent integration, but also suppress tracks swap or mispairing among multiple frames when the targets are close. Numerical results and tests with real radar data for various multitarget scenarios are provided to demonstrate the effectiveness of the proposed algorithms.

Synthetic aperture radar (SAR) imaging with sub-Nyquist sampled echo is a challenging task. Compressed sensing (CS) has been widely applied in this case to reconstruct the unambiguous image. The CS-based methods need to set the iterative parameters manually, but the appropriate parameters are usually difficult to obtain. Besides, such methods require a large number of iterations to obtain satisfactory results, which seriously restricts their practical applications. Moreover, the observation scene of SAR is not sparse in some cases. In this paper, we aim at proposing an efficient and effective imaging method for non-sparse observation scenes with reduced data. Firstly, considering the characteristics of non-sparse observation scenes in SAR imaging, we model the SAR imaging problem as a joint low-rank and sparse matrices recovery problem. After that, the iterative alternating direction method of multipliers (ADMM) to solve the above problem is unrolled into a layer-fixed deep neural network with trainable parameters, in which the learnable parameters are layer-varied. The threshold parameters, as well as the weight parameter between the sparse part and low-rank part of each layer, are learned adaptively instead of manually tuned. Experiments prove that the proposed LRSR-ADMM-Net is capable of reconstructing the non-sparse observed scene with high efficiency and precision. Particularly, the proposed LRSR-ADMM-Net yields better reconstruction performance while maintaining high computational efficiency compared with the state-of-the-art iterative recovery methods and the trainable sparse-based network methods.

Video synthetic aperture radar (SAR) receives more and more attention in recent years because it can provide continuous images of the observed scene. However, the enormous data of video SAR to obtain the multiframe images bring big challenges to its transmission, storage, and processing, especially for small unmanned aerial vehicle (UAV) platform. In this article, we aim at proposing an efficient video formation method for video SAR systems with reduced data. First, the characteristics of video SAR observed scene are analyzed. It is found that the observed scene with multiple frames can be modeled as the sum of a low-rank tensor and a sparse tensor efficiently. After that, the video formation problem for video SAR is modeled as a joint low-rank and sparse tensors recovery problem. Finally, an efficient tensor alternating direction method of multiplier is proposed to obtain the final SAR video. Compared with the traditional frequency- or time-domain imaging methods, the amount of data samples can be greatly reduced. On the other hand, the proposed method outperforms the state-of-the-art SAR imaging methods with reduced samples, including the joint low-rank and sparse matrices recovery method and the low-rank tensor recovery method. Numerical simulations validate the effectiveness of the proposed method.

Geosynchronous spaceborne–airborne bistatic synthetic aperture radar (GEO-SA-BiSAR) consists of a GEO transmitter and airborne receiver, which has extensive application prospects in both civilian and military fields for its ability to generate high-resolution images of the ground target with frequent coverage and abundant scattering information. However, the Doppler bandwidth in this configuration exceeds the transmitted pulse repetition frequency (PRF), which leads to sub-Nyquist sampling. To solve this problem, a multireceiving technique has been applied to the receiver to increase the equivalent sampling rate and reconstruct an unambiguous image. In this article, we take a different approach to recover the unambiguous image for GEO-SA-BiSAR with fewer receiving channels. First, the accurate echo model is established based on the “non-stop-and-go” propagation delay model to lay the foundation of accurate imaging. After that, the GEO-SA-BiSAR imaging problem is modeled as a problem of joint sparse and low-rank matrices’ recovery. To reduce the computing time of the traditional recovery method, a modified alternating direction method of multipliers (M-ADMM) is proposed, where the computation and storage of the computational expensive observation matrix are avoided. Furthermore, an M-ADMM method with multiple receiving channels, which combines the recovery theory and multireceiving information, is also proposed to handle the severe sub-Nyquist sampling echo of GEO-SA-BiSAR. Simulation results reveal that the proposed method can recover the original image scene with high computational efficiency. Meanwhile, the number of receiving channels can be reduced compared with the multireceiving technique.

The multi-frame detection (MFD) with range-Doppler-azimuth measurements has been shown to be significant in detecting and tracking weak targets in active radar and sonar systems. Existing methods suffer from integrated energy loss for a long time noncoherent observation sequences due to approximate target evolution model or rough energy integration strategies. Moreover, it is hard to maintain consistency of multi-frame integration for targets in different near-field and far-field regions. By carefully mapping echo measurements to a discrete grid space without the introduction of new conversion errors, we proposed an efficient solution to build an accurate grid state model based on sensor parameters. Then, the combination of the grid state model and target evolution relationship among adjacent frames enables an adaptive MFD implementation. Each search path during multi-frame integration is adjusted adaptively with different grid state sizes. Finally, an improved strategy based on the predicted estimate is further presented to reduce the complexity of algorithms and improve the accuracy of possible search paths. The proposed methods can effectively integrate target energies among multi-frame range-Doppler-azimuth measurements, and maintain the robustness of the long time integration for targets in different near-field and far-field regions. Numerical results and tests with real radar data further show that the proposed method achieves high detection probability and tracking accuracy for weak targets with range-Doppler-azimuth measurements.

In this paper, we investigate the uplink communication of a reconfigurable intelligent surface (RIS) assisted system, in which an user equipment (UE) with single radio frequency (RF) chain delivers information to an access point (AP) by adopting the spatial modulation (SM). Specifically, we first investigate the transmit SM (TSM) scheme and jointly optimize the UE’s power allocation matrix and the RIS reflection coefficients to enhance the system reliability. We formulate a non-convex optimization problem to reduce the system symbol-error-rate (SER) and propose a novel penalty-alternative optimizing algorithm to obtain a near-optimal solution. Following this, we show that with the assistant of RIS, receive SM (RSM) scheme can also be performed even if the UE has only one RF chain. Based on this observation, a novel RIS-assisted RSM scheme is proposed, which can provide a low cost and complexity solution for system realization. The reflection coefficients of the RIS are also optimized for the proposed RSM. Numerical results show that the RIS-assisted TSM can achieve a lower SER than the conventional communication scheme (CTS) without SM and the proposed RSM scheme has lower detection complexity than that of CTS. It is also shown that the performance of the TSM and RSM schemes is more sensitive to the quantization accuracy of the phase of the RIS coefficients than that of the amplitude.

Low-earth-orbit (LEO) synthetic aperture radar (SAR) can achieve advanced remote sensing applications benefiting from the large beam coverage and long duration time of interested area provided by a geosynchronous (GEO) SAR illuminator. In addition, the receiving LEO SAR system is also cost-effective because the transmitting module can be omitted. In this article, an imaging method for GEO-LEO bistatic SAR (BiSAR) is proposed. First, the propagation delay characteristics of GEO-LEO BiSAR are studied. It is found that the traditional “stop-and-go” propagation delay assumption is not appropriate due to the long transmitting path and high speed of the LEO SAR receiver. Then, an improved propagation delay model and the corresponding range model for GEO-LEO BiSAR are established to lay the foundation of accurate imaging. After analyzing the sampling characteristics of GEO-LEO BiSAR, it is found that only 12.5% sampling data can be acquired in the azimuth direction. To handle the serious sub-Nyquist sampling problem and achieve good focusing results, an imaging method combined with multireceiving technique and compressed sensing is proposed. The multireceiving observation model is first obtained based on the inverse process of a nonlinear chirp-scaling imaging method, which can handle 2-D space-variant echo. Following that, the imaging problem of GEO-LEO BiSAR is converted to an L1regularization problem. Finally, an effective recovery method named complex approximate message passing (CAMP) is applied to obtain the final nonambiguous image. Simulation results show that the proposed method can suppress eight times Doppler ambiguity and obtain the well-focused image with three receiving channels. With the proposed method, the number of required receiving channels can be greatly reduced.

In synthetic aperture radar (SAR) imaging, moving target is generally mixed with stationary targets. Meanwhile, the image of a moving target is distorted and displaced due to the lack of its prior velocity information. Furthermore, imaging of a moving target for geosynchronous (GEO) spaceborne-airborne bistatic SAR (GEO SA-BiSAR) is a more challenging problem because the echo is sub-Nyquist sampled in azimuth. In this article, a simultaneous moving and stationary target imaging method for GEO SA-BiSAR is proposed. First, range models and the corresponding echo models of moving and stationary targets are established. The observation models for both moving and stationary targets with two receiving channels are derived based on the inverse of an efficient imaging algorithm. After that, the imaging problem of moving and stationary targets is modeled as a joint velocity estimation and sparse decomposition problem, which aims at optimizing the entropy of the moving target image and residual error of the formed images at the same time. Finally, a joint optimization method based on the particle swarm optimization (PSO) method and alternating direction method of multipliers (ADMM) is applied to achieve the imaging of moving and stationary targets and estimation of the moving target velocity. With two receiving channels, the accurate separation and focusing of stationary and moving targets as well as the precise estimation of moving target velocity can be achieved with sub-Nyquist sampling echo. Simulation results are presented to validate the effectiveness of the proposed method.

In this paper, non-orthogonal multiple access (NOMA) networks assisted by multiple intelligent reflecting surfaces (IRSs) with discrete phase shifts are investigated, in which each user device (UD) is served by an IRS to improve the quality of the received signal. Two scenarios are considered according to whether there is a direct link between the base station (BS) and each UD, and the outage performance is analyzed for each of them. Specifically, the asymptotic expressions for the upper and lower bounds of the outage probability in the high signal-to-noise ratio (SNR) regime are derived. Following that, the diversity order is obtained. It is shown that the use of discrete phase shifts does not degrade diversity order. More importantly, simulation results reveal that a 3-bit resolution for discrete phase shifts is sufficient to achieve near-optimal outage performance. Simulation results also imply the superiority of IRSs over full-duplex decode-and-forward relays.

Intelligent reflecting surfaces (IRSs) are envisioned to provide reconfigurable wireless environments for future communication networks. In this paper, both downlink and uplink IRS-aided non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) networks are studied, in which an IRS is deployed to enhance the coverage by assisting a cell-edge user device (UD) to communicate with the base station (BS). To characterize system performance, new channel statistics of the BS-IRS-UD link with Nakagami-$m$fading are investigated. For each scenario, the closed-form expressions for the outage probability and ergodic rate are derived. To gain further insight, the diversity order and high signal-to-noise ratio (SNR) slope for each scenario are obtained according to asymptotic approximations in the high-SNR regime. It is demonstrated that the diversity order is affected by the number of IRS reflecting elements and Nakagami fading parameters, but the high-SNR slope is not related to these parameters. Simulation results validate our analysis and reveal the superiority of the IRS over the full-duplex decode-and-forward relay.

In this paper, a downlink non-orthogonal multiple access (NOMA) system is studied, in which an intelligent reflecting surface (IRS) is deployed to enhance the coverage by assisting a cell-edge user device (UD) to communicate with the base station (BS). To characterize system performance, new channel statistics for the BS-IRS-UD link with Nakagami-m fading are investigated. Based on the new channel statistics, the closed-form expression for the outage probability is derived. To gain further insight into the problem, the diversity order is obtained according to the asymptotic approximation in the high signal-to-noise ratio (SNR) regime. It is demonstrated that the diversity order is affected by the number of IRS elements and Nakagami fading parameters. Simulation results validate our analysis and reveal the superiority of the IRS over the full-duplex decode-and-forward relay in the high-SNR regime.

In this paper, we investigate the uplink of a millimeter-wave (mmWave) communication system, in which small base stations (SBSs) are densely placed. The positions of the SBSs are modeled as a homogeneous Poisson point process (PPP) and a user equipment (UE) connects to multiple SBSs opportunistically and adopts the spatial modulation (SM) scheme. Two detection methods, namely the centralized detection and distributed detection, are first proposed for the SBSs to demodulate the received signal and the power allocation scheme minimizing the system symbol error rate (SER) is investigated. Following this, by ignoring the side lobe of the UE, the probability that the SM scheme outperforms the conventional transmission scheme in which the UE only communicates with the SBS with a stronger channel is approximated to evaluate the performance of the SM scheme. Numerical results show that the SM scheme can effectively improve reliability of the system.

Heterogeneous cellular networks (HCNs) present an attractive solution to increased demands in mobile user capacity. Comprehensive studies have been conducted in stochastic geometric models that represent the relatively random placement of base transmitting stations (BTSs) operating at different power levels. This study considers the design of two‐tier HCNs for which picocell BTSs from the second tier are separated simultaneously from each other and from their tier‐1 macrocell counterparts. These separations, introduced in detail in the study, are termed the co‐tier and cross‐tier separations, with each parameter characterised by a minimum distance separation. Subsequently, expressions are obtained for distance distributions of BTSs from specific tiers to typical users, followed by conditional probabilities of association with each tier. We show that a minimum radius of association can be guaranteed for a tier‐2 BTS based on the values of co‐tier and cross‐tier separations. Furthermore, we analyse the Laplace transform of interference to the typical user and the resultant formulae for coverage probability, and by extension, area spectral efficiency. Numerical results demonstrating the effect of co‐tier and cross‐tier separation on these performance parameters support the analysis and provide insights into cell planning based on this concept.

A joint user clustering and subcarrier allocation scheme for downlink non-orthogonal multiple access (NOMA) systems is examined in this paper. We propose the scheme for downlink NOMA systems which maximizes the achievable diversity order. The closed-form expression of the outage probability of the worst-performance user in the worst case is derived and validated by simulations. Numerical results show that the proposed scheme can achieve the same diversity order as the exhaustive searching scheme.

Homogeneous user models have been traditionally considered in heterogeneous cellular networks (HCNs) that comprise base transmitting stations (BTSs) operating at different power levels. As small-cell BTSs are usually deployed to cater to dense user clusters in limited spaces, Poisson cluster processes (PCPs) have found application in modeling non-homogeneous user distributions, for which deployments are placed at the center of user clusters. We propose a two-tier HCN model that comprises a single potential tier-2 small-cell deployment per user cluster. The potential tier-2 BTS deployments are offset by a randomly distributed distance with respect to the centers of their corresponding clusters, which are also known as social attractors (SAs). Deployment or active transmission of a tier-2 BTS may only occur if there is sufficient separation from active tier-1 BTSs in the network, effectively creating a Poisson hole process (PHP) of tier-2 BTSs. By using variations of the PCP to model clustered users that surround SAs, distance distributions are analyzed for two situations, where the offset between an SA and a potential tier-2 BTS is modeled by using the uniform and Gaussian distributions, respectively. This result is extended to obtain the probability of association of users to their corresponding cluster deployments, and the two BTS tiers.

In this paper, we investigate physical layer security in a two-tier heterogeneous network with sub-6 GHz massive multi-input multi-output (MIMO) macro cells and millimeter wave (mmWave) small cells. By considering pilot attacks from the eavesdroppers, we analyze the coverage and secrecy performance using stochastic geometry. For the sub-6 GHz tier, we show that increasing the number of BS antennas is more effective than increasing BS density in improving the coverage performance, whereas densifying BS is more effective for security enhancement. For the mmWave tier, we first derive the success probability of beam alignment based on a beam sweeping-based channel training model. It is shown that the mmWave tier may outperform the sub-6 GHz counterpart in terms of both coverage and secrecy through densifying the base stations. Our results also reveal that the mmWave small cell can provide better coverage performance in the high transmission rate region, and can achieve higher security in the low redundant rate region, which reveals the advantage of using mmWave for secure communication. Numerical results verify the analysis.

In this paper, the impact of adaptive smarter eavesdroppers on the secrecy performance of a multi-antenna cellular network is investigated. The eavesdroppers can act as either passive eavesdroppers or active jammers based on their distance to the active base stations (BSs). To analyze the secrecy performance, the BSs, cellular users, and eavesdroppers are modeled as independent Poisson point processes. The closed-form expressions of the connection outage probability and lower bound of the secrecy outage probability are derived using the stochastic geometry approach. Following that, the conditions under which the eavesdroppers can act as active jammers are obtained. Finally, the optimal power allocation between artificial noise and information signal and the secrecy code rate at each BS, as well as the guard zone of the eavesdroppers are obtained using the Stackelberg game approach, where the eavesdroppers are modeled as the leader and the BSs as the follower. The Stackelberg equilibrium is obtained through the proposed iterative algorithm. Numerical results verify the theoretical analysis and show that the secrecy performance can be degraded severely by the adaptive eavesdroppers.

We derive tractable bound expressions on achievable spectral efficiency for a multiple-input multiple-output (MIMO) system with a signal-to-leakage-plus-noise ratio precoding scheme (SLNR-PS) under the condition of imperfect channel state information. These bounds are tight and approach exact values when the number of base station (BS) antennas is large. A problem of energy efficiency (EE) maximization is investigated by using a practical power consumption model. The effects of the system parameters and quality of channel estimation, including the number of BS antennas, transmit power, and training length on the performance metrics, are explicitly analyzed. Following that, an alternating optimization algorithm is employed to obtain the optimum EE. It has been shown that the proposed SLNR-PS performs better than the matched-filtering and zero-forcing schemes and a deployment of massive MIMO with the optimal transmit power and training length can achieve high EE.

In this paper, the security issue in a multi- input-single-output (MISO) system in the presence of multiple randomly distributed eavesdroppers (Eves) is investigated. The Eves are distributed according to a Poisson Point Process (PPP) and each of them can operate in either a half-duplex (HD) or full-duplex (FD) mode. For a FD-mode Eve, it can overhear the secret information transmission and send some jamming signals simultaneously to degrade the reception of Bob. Based on the stochastic geometry method, we first derive the cumulative distribution function (cdf) expressions of the signal-to-interference-plus- noise ratio (SINR) for Bob and Eves. Following that, a lower bound of the intercept probability is obtained. Some important properties are derived, which provide very useful insights. Finally, the optimal power allocation of Alice and the optimal fraction of FD-mode Eves are solved by using a game-theoretical approach. Simulation results are shown to validate the theoretical analysis.

In this paper, the security in a device-to-device (D2D) spectrum sharing network is investigated. The cellular users and eavesdroppers are distributed according to two independent Poisson Point Processes (PPPs), and the positions of the D2D transmitters follow a hard-core point process. Based on the stochastic geometry, we first derive closed-form expressions of the connection and secrecy outage probabilities of a typical user and then analyze the impacts of different parameters. We also derive the connection probability of a D2D user, which is shown to be independent of the parameters of the base station (BS). Following that, we analyze the impact of D2D transmissions on the power allocation at the BS and derive the optimal power allocation solution for the fixed-rate transmission scheme. Simulation results validate the analysis.

In this paper, physical layer security in multi-antenna small-cell networks is investigated, where the multi-antenna base stations (BSs), cellular users, and eavesdroppers are all randomly distributed according to three independent Poisson point processes. To improve the secrecy performance, artificial noise (AN) aided transmission is adopted at each BS. Based on the stochastic geometry, we first derive the closed-form expressions of the connection and secrecy outage probabilities, and then comprehensively analyze the impact of different parameters through asymptotic analysis. It shows that in a low cell-load case, deploying more BSs will improve the connection and secrecy outage performance, and deploying more transmit antennas at each BS will only improve the connection outage performance. For a fixed-rate transmission, the condition under which AN becomes unnecessary is derived. We also derive a semi closed-form expression of the lower bound of the achievable average secrecy rate, which is numerically efficient to evaluate. Finally, we extend the study to a high cell-load case and adopt the zero-forcing beamforming scheme to support multi-user transmission. The connection and secrecy outage probabilities are also analyzed. Moreover, the optimal number of users maximizing the secrecy area spectral efficiency is discussed, and it is shown to be a fixed portion of the number of transmit antennas. Simulation results are presented to validate the theoretical analysis.

In this paper, the secure transmission strategy for a multi-input-single-output multi-eavesdropper system with coexistence of a secure user (Bob) and a normal user (NU) is investigated. The NU and Bob require normal and secure data transmissions, respectively, and thus, the stream for the NU can be exploited to confuse the eavesdroppers. To guarantee the security of Bob, artificial noise (AN) is also deliberately injected into the null space of Bob and NU. The power allocation among Bob, NU, and AN, as well as the wiretap code rates, is jointly optimized to maximize the effective secrecy throughput (EST), under the average throughput constraint of the NU and statistical channel state information (CSI) of eavesdroppers. Both non-adaptive and adaptive transmission schemes are proposed, based on the statistical and instantaneous CSI of the legitimate channels, respectively. An alternative optimization algorithm is proposed to obtain the optimal parameters. It is proved that the EST is a quasi-concave function of the secrecy rate and the power allocated to Bob, and for fixed wiretap code rates, the optimal power allocation is derived in a closed-form expression. Numerical results show that the EST increases with the increase in transmitting power and the number of transmit antennas, and decreases with the increasing throughput constraint of the NU. Improved EST can be achieved through injecting AN and concurrent transmission of Bob and NU.

In this paper, the security of multi-input single- output (MISO) amplify-and-forward relaying network with untrustworthy relay nodes is considered, where the untrustworthy nodes can help to forward the received signal and they may also try to decode such information, which can be regarded as potential eavesdroppers (Eves). To deal with such kind of smarter Eves, relay selection is adopted and both the maximal-ratio transmission (MRT) scheme and the zero-forcing beamforming (ZFBF) scheme are used at the multi-antenna base station (BS). To achieve a positive secrecy capacity, the destination also injects intended jamming signal to confuse the decoding of the untrustworthy nodes. Either approximation or lower bound of the secrecy outage probability is derived in closed form. It is shown that the proposed partial relay selection scheme approaches the optimal relay selection scheme. In particular, for the ZFBF scheme, when the number of antennas is large enough, increasing the number of relay nodes will increase the diversity order and thus improves the secrecy performance. Simulation results validate the effectiveness of the scheme and correctness of analysis.

In this paper, we study a wireless-powered cooperative relaying system which consists of a source node (SN), a relay node (RN) and a destination node (DN). The RN has no embedded power supply, thus it needs to harvest energy from the radio signal transmitted by a power beacon (PB) which is responsible for charging the RN before forwarding the information to the DN. In addition, we assume that the RN possesses a buffer and can temporarily store the information received from the SN. Based on this assumption, we propose an adaptive transmission scheme in which the system adaptively switches between two transmission modes, namely the SN information transmission (SN-IT) mode and the RN harvest-and-transmit (RN-HAT) mode. The optimal mode adaptation method that maximizes the throughput of the system is obtained for different system setups and the throughput of the system is obtained in closed-form expressions. Numerical results are provided to verify the analytical expressions. It is shown that the throughput of the wireless-powered cooperative relaying system can be improved by using the proposed adaptive transmission scheme.

In this study, the authors present asymptotic capacity analysis of block diagonalisation (BD)‐precoding and BD with space‐time block code schemes for future wireless communication systems. Assuming that the number of base station antennas N and the number of antennas per user M are large while their ratio remains bounded, the capacity expressions for these two schemes are derived in both cases of perfect channel state information (CSI) and imperfect CSI, respectively. Based on this, the authors obtain the optimal number of user terminals K to be served by the system. Closed‐form expressions of the optimum training length based on the basic system parameters are derived for practical implementation. The accuracy of the analysis is validated by numerical results with different parameter settings. It has been shown that the capacity expressions are accurate even for small M .

We propose a double-modulated frequency modulation waveform for multiple-input multiple-output radars. The transmitted waveforms are divided into two segments with the same bandwidth and different durations. The durations of all the segments among different waveforms are used to optimize the performance. Theoretical analyses are provided to study the relationships between the autocorrelation/cross-correlation functions and parameters such as bandwidth, pulse duration, and segment durations. Numerical results show that the proposed waveform has low cross correlation even with Doppler shifts. The autocorrelation sidelobes, cross-correlation levels, and range sidelobes of the proposed waveform reduce with the increase in the time-bandwidth product.

We consider a wireless-powered relaying system in which the relay nodes (RNs) that have no embedded power supply are charged by the radio frequency signal transmitted by a power beacon. Each RN is assumed to possess a buffer and can temporarily store the information received from the source node. Based on this assumption, we propose an adaptive transmission scheme, in which each RN adaptively switches between two transmission modes. To maximize the system throughput, a joint node-and-mode selection scheme in which the RN and its transmission mode are jointly selected in each time slot is investigated. For the general system setup, some analytical results are obtained, which provide useful insights in finding the optimal joint node-and-mode selection scheme. Following this, the analysis is applied to two specific systems, the single RN system and the multiple RNs system with a symmetric channel. For these system setups, the system throughput and the corresponding optimal transmission scheme are obtained in the closed-form expressions. Numerical results show that the throughput of the wireless-powered relaying system can be improved by using the proposed transmission schemes.

In this paper, the security aspect of an amplify-and-forward relaying network with untrusted relay nodes is considered. The untrusted nodes can help to forward the received signal and they may also try to decode such information, which can be regarded as potential eavesdroppers (Eves). To deal with such a challenging issue, a successive relaying scheme is adopted, where the multi-antenna source transmits to two selected nodes alternately, and the conventional detrimental inter-relay interference is used to jam the untrusted nodes without external helpers. Considering different complexity requirements, several relay selection schemes are proposed, and the closed-form expressions of the lower bound of secrecy outage probability are derived accordingly. To obtain some insights for the network design, an asymptotic analysis is also given, which shows that the maximum secrecy diversity order of N-1 can be achieved, where N is the number of the untrusted relays. Moreover, the spectral efficiency is improved dramatically with the successive relaying scheme. Simulation results show that the proposed max-min scheme has almost the same performance as that of the optimal one, and the theoretical results match well with the simulation results.

In this paper, we study a wireless powered co-operative communication system, which consists of a hybrid relay node (RN), a source node (SN), and a destination node (DN). It is assumed that the hybrid RN has a constant power supply while the SN has no embedded power supply. Thus, the SN needs to first harvest energy from the radio frequency (RF) signal broadcasted by the hybrid RN before transmitting information to the hybrid RN. By assuming that the RN has an information buffer and can temporarily store the information it received, we investigate the long-term throughput of two different block-wise cooperative protocols, namely the block-wise harvest-and-transmit (BW-HaT) protocol and the block-wise mode adaptation (BW-MA) protocol. For the BW-HaT protocol, the throughput expression is obtained in closed form. For the BW-MA protocol, the optimal mode adaptation method that maximizes the throughput of the system is presented and the maximum throughput is given for different system setups. It is shown that through simultaneously transmitting information and energy to the DN and SN, respectively, the proposed transmission schemes can significantly increase the system throughput.

In this paper, we study an energy-harvesting cognitive radio (CR) system where each secondary user (SU) harvests energy to recharge its battery. Cooperative spectrum sensing is employed to enhance the sensing performance. In this energy- constrained scenario, the SUs, as per their energy-arrival rates, can cooperate to achieve higher opportunistic spectrum utilization and improved primary user (PU) detection. For a heterogeneous CR system with different sensing environment and energy-arrival process at each SU, the optimal probability of sensing is obtained for each SU to maximize the SU network throughput while satisfying the PU collision and energy-causality constraints. SOSTOOLS is employed to solve the polynomial optimization problem, and a suboptimal scheme which can be used for larger systems is proposed. Furthermore, under a homogeneous scenario, it is shown that with a minimum number of SUs cooperating, the CR throughput performance can overcome the energy- causality and PU collision constraints.

In this paper, we consider a relaying system which consists of a multiple-antenna source node (SN), M single-antenna destination nodes (DNs) and a multiple-antenna relay node (RN). The RN possesses a buffer and it is able to store the decoded message before retransmitting the message to the DNs. We use the joint link-and-user scheduling method to maximize the long term average achievable rate of a multiple-input multiple-output (MIMO) relaying system. The optimal scheduling criteria is obtained and a two-step approach is proposed to implement it. In addition, we propose a rate allocation scheme of the source-relay (S-R) link to preserve the flow conservation constraint of each individual user. Furthermore, two reduced complexity joint link-and-user scheduling methods which use the zero forcing (ZF) beamforming in the relay-destination (RD) link are investigated. It is shown that joint link-and-user scheduling can significantly increase the average achievable rate of the system.

A novel beamforming (BF) receiver with adaptive detection (AD), which can effectively switch between a maximum-likelihood (ML) detection and a zero-forcing (ZF) detection based on instantaneous spatial conditions, is presented for a large-scale MIMO communication system over fading channels. The proposed system divides all receive antennas into many adaptive beamformers (ABFs) to reduce the array dimensions in order to simplify the signal detection process and employ the adaptivity benefits. The effects of different system configurations on symbol-error rate (SER) performance have been examined. It has been shown that the proposed MIMO system provides comparable SER performance, but with a remarkable complexity reduction as compared to that of the conventional ML receiver.

Over the past few decades, frequency hopping (FH) techniques have attracted considerable interest in both military and commercial communications. However, fading and interference can significantly degrade the performance of an FH system. One method commonly employed to overcome the degradation in performance because of the fading is the use of diversity. Furthermore, fast FH (FFH) systems can enjoy both time and frequency diversity and hence FFH systems employed in conjunction with diversity‐combining techniques are effective for combating fading and interference effects. In this study, the authors provide a comprehensive survey on the past and current research work on diversity‐combining techniques for suppressing different types of interference in FFH M ‐ary frequency‐shift‐keying systems over various fading channels. Some commonly used theoretical approaches for analysing performance of FFH systems are also presented. In addition to the survey, they will also discuss some interesting areas of future work in this research topic.

A novel adaptive beamforming (BF) receiver is proposed for a multiple‐input–multiple‐output communication system over multipath fading channels. By dividing a large number of receive antennas into many adaptive beamformers (ABFs), the proposed system reduces the array dimension in order to simplify the signal detection process and enjoys the benefit of BF techniques to improve the symbol‐error‐rate (SER) performance. The effectiveness of the proposed system depends on the number of ABFs and the number of antennas per ABF. The statistical properties of complex Wishart matrices are applied to analyse the SER performance of the proposed system with both maximum‐likelihood (ML) detection and zero‐forcing detection. Furthermore, the authors have derived an upper bound for SER of the ML detection based on the smallest eigenvalue distribution. Through the authors analysis, it has been shown that the proposed system using ML detection provides comparable SER performance, but with a lower complexity as compared with that of a conventional ML receiver because of reduced array dimensions.

In this paper, we propose a buffer state based relay selection scheme for a finite buffer-aided cooperative relaying system. Our proposed relay selection scheme selects a relay node based on both the channel quality and the buffer state of the relay nodes. The Markov chain model is adopted to analyze the buffer state transition properties and the outage probability of the proposed relay selection scheme is obtained in a closed-form expression. Our analytical results show that if the buffer size of each relay node is greater than 2, the proposed relay selection scheme can achieve full diversity. Furthermore, it is shown that our proposed relay selection scheme has lower average packet delay compared with the max-link relay selection scheme. In addition, the average packet delay of the proposed relay selection scheme does not increase as the buffer size increases.

In this study, the authors investigate the diversity‐multiplexing tradeoff (DMT) of a wireless system in which user equipments (UEs) are equipped with only one antenna while the destination has multiple antennas. Each UE is assisted by M half‐duplex cooperative users serving as relay nodes. They combine the opportunistic relaying scheme and the cooperative spatial multiplexing (C‐SM) scheme to produce an opportunistic C‐SM (OC‐SM) scheme. The fraction of time allocated to the source–relay link and the relay–destination link is treated as a design parameter to minimise the outage probability of the system. At high signal‐to‐noise ratio regime, the optimal time allocated factor is obtained in a closed‐form expression through DMT analysis. Based on the DMT result of the proposed OC‐SM scheme, an adaptive OC‐SM (AOC‐SM) approach in which the system can switch between different C‐SM models adaptively based on the rate transmitted is proposed. To reduce the complexity of the relay nodes, an AOC‐SM scheme with relay selection (SAOC‐SM) in which a constant number of relay nodes is selected from the set of relay nodes that have successfully decoded the source message is investigated. The DMT results of the SAOC‐SM scheme and the AOC‐SM scheme are obtained and compared.

The authors consider the problem of energy consumption in a multiband cognitive radio network, in which a secondary user can sense multiple frequency bands authorised to the primary user (PU) before it decides to access some frequency bands and keep the interference introduced to the PU under a certain threshold. The sensing time and power allocation need to be designed carefully to reduce the energy consumption. Therefore they identify the optimal sensing time and accessing power to minimise the energy consumption of the cognitive radio that simultaneously senses and accesses multiple bands under the multiband sensing‐based spectrum sharing scheme. To obtain the optimal solution, they transform the original problem formulated as the ratio of two functions into another parametric formulation. The interference power is considered as one of constraints in the author's scheme in order to protect the PU. The algorithm of optimal sensing time and power allocation is proposed for the multiband cognitive radio system. Furthermore, they discuss the effect of channel number, interference power and gain estimation of channels on energy consumption and optimal sensing time and validate their schemes and analysis by simulation results.

A novel limited feedback strategy based on a compressive sensing technique is proposed for the downlink large‐scale multiple‐input single‐output (MISO) system. The effectiveness of transmit beamformers relies on the feedback quality of channel state information (CSI). The instantaneous CSI is compressed and sent back to the base station (BS) by receivers. An efficient recovery algorithm is applied at the BS in the presence of measurement noise and feedback link noise. The proposed feedback strategy can provide the BS with much more precise CSI as compared with some conventional vector quantisation schemes. The proposed scheme also has lower‐computational complexity. Furthermore, the authors derive a tight lower bound on the user sum rate, assuming that zero‐forcing beamforming is applied at the BS, and that active users are semi‐orthogonal to each other. Numerical results show that the proposed compressive sensing‐based limited feedback scheme yields better performance gain than the conventional channel quantisation approaches.

In this letter, we modify the transmitted signal of the discrete frequency coding waveform with linear frequency modulation (DFCW-LFM) for multiple-input multiple-output (MIMO) radar from contiguous subpulses to an inconsecutive pulse train. The range-Doppler map is obtained by performing fast Fourier transform (FFT) after the transmit beamformer to detect the moving target. The cost function of the genetic algorithm used to optimize the carrier frequency sequence is obtained by minimizing both the range-Doppler sidelobes and cross-correlation peaks. Compared with the DFCW-LFM, the proposed waveform has lower autocorrelation sidelobes and cross-correlation for the delay within the subpulse duration.

In this paper, we propose a novel coordinated downlink beamforming strategy based on the semidefinite relaxation (SDR) approach for a clustered multicell cellular system. As base station (BS) cooperation can provide significant performance improvement for the system capacity and interference suppression, we divide the whole network into a number of clusters. In each cluster, several BSs share the common user data and cooperatively design their signaling strategies. In this system, maximizing the sum-rate requires solving a global nonconvex optimization problem. We apply the semidefinite programming (SDP) relaxation to convert the original problem into distributed convex SDP which can be solved efficiently and optimally with convex optimization techniques. Numerical results show that the proposed beamforming algorithm provides a remarkable sum-rate enhancement and outperforms some existing schemes.

In this study, the authors present an algorithm to detect unknown interference in slow frequency‐hopped quadrature phase‐shift‐keying systems. Both partial‐band noise interference and multitone interference are considered. The algorithm is developed based on the correlator outputs over one hop. A suitable threshold level is derived for detection. The authors formulate the analytical expressions for probability of detection for both interference models. Numerical results reveal that the proposed algorithm can detect both interference types even at low interference power.

A low‐complexity channel estimation algorithm is proposed to improve performance of two high frequency standardised waveforms: MIL‐STD‐188‐110B Appendix C standard and STANAG 4285. In the proposed estimation algorithm, the channel impulse response is modelled as a linear‐time function within a frame and the least square criterion is adopted. With the estimated CIRs, the authors study and compare bit‐error‐rate (BER) performance and complexity of three turbo equalisation (TEQ) schemes, including the minimum mean‐square error (MMSE), the MMSE with decision feedback equalisation (DFE) (MMSE‐DFE) and the soft‐feedback interference‐cancellation (SFIC) turbo receivers. The authors then propose a hybrid TEQ scheme that uses the MMSE‐DFE equaliser for the first iteration and the SFIC equaliser for the rest. Simulation results show that the proposed channel estimation algorithm performs well and the TEQ schemes realise a significant performance improvement as compared with a non‐iterative receiver. Moreover, the proposed hybrid TEQ scheme achieves the best trade‐off between BER and complexity for the MIL‐STD‐188‐110B Appendix C standard, whereas the SFIC‐TEQ scheme is optimal for the STANAG 4285 standard.

In this study, the authors focus on energy efficiency of a cognitive radio (CR) system, in which a secondary user (SU) senses periodically and accesses opportunistically a specific band authorised to a primary user (PU). Based on a generalised expression of energy consumption, we jointly optimise sensing, transmission and frame durations to maximise the energy efficiency for a CR system and investigate the performance of the proposed design over Rayleigh fading channels. The problem of energy efficiency is formulated as a function of sensing and transmission durations with the constraints on the interference to the PU. To protect the PU, we limit the detection probability as well as restrict the interference caused by the SU because of the re‐occupancy of the PU. In a generalised model, energy consumptions of sensing, transmission and idling state need to be considered for the SU. The optimal sensing and transmission durations are obtained by a sub‐optimal iterative algorithm. The performance of energy efficiency and duration of the SU over a Rayleigh‐faded channel is investigated. Numerical results show that the proposed reduced‐complexity approach performs comparably with that of the exhaustive search algorithm.

In this study, the authors propose a diversity‐combining scheme with transmit antenna selection (TAS) and output‐threshold generalised selection combining (OT‐GSC) receiver. It is shown that the proposed TAS/OT‐GSC can achieve similar performance as compared to the TAS/GSC with a reduced number of channel estimates when the predetermined signal‐to‐noise ratio (SNR) threshold is optimised. The outage probability, average output SNR, and symbol‐error rate (SER) expressions of the proposed TAS/OT‐GSC scheme are derived and presented over independent and non‐identically distributed Rayleigh‐fading channels. The analytical expressions are validated by simulation results. The trade‐off comparisons in terms of the SER and number of channel estimates between the TAS/OT‐GSC and TAS/GSC are discussed. Lastly, the capacity between the TAS/OT‐GSC and TAS/GSC is compared.

The composite effect of hostile multitone jamming and partial-band noise jamming on bit-error rate (BER) performance of a fast frequency-hoppedM-ary frequency-shift-keying system is studied over Rayleigh fading channels in the presence of timing and frequency offsets. The maximum-likelihood (ML) diversity-combining method is employed to improve BER performance of the system. Analytical BER expression of the proposed ML receiver is derived. The analytical results, validated by computer simulation, show that the proposed ML receiver can suppress the composite hostile jamming more effectively than some existing conventional diversity-combining receivers. The ML receiver is also found to be robust against inaccurate estimation of the required side information.

In this paper, we propose a detection algorithm to detect unknown partial-band noise interference (PBNI) which is frequently encountered in slow frequency-hopped spread spectrum (SFH-SS) systems. The algorithm utilizes a simple hypothesis testing to decide presence of PBNI in any particular hop after dehopping. A suitable threshold level is first derived to detect the PBNI by analyzing the statistical property of the outputs of two correlators used for quadrature phase-shift-keying (QPSK) demodulation. Then, the proposed detector is developed by summing the outputs of the correlators over one hop duration. We also formulate an expression for probability of detection (PD) and use it as a performance measure for detection. Analytical and simulation results show that the proposed detector is able to detect the PBNI very well even at low interference power (8 dB lower than signal power). In addition, numerical results reveal that the proposed algorithm can also be used to detect multitone interference (MTI) encountered in slow FH-SS systems.

Iterative equalization techniques are effective in mitigating inter-symbol interference (ISI). In this paper, we first study and compare three low-complexity adaptive-channel-estimation-based turbo equalization (ACE-based TEQ) algorithms over high-frequency (HF) waveform channels based on the STANAG 4285 standard. These reduced-complexity equalization algorithms include the minimum mean-square error (MMSE), the MMSE decision feedback equalization (MMSE-DFE) and the soft feedback interference cancellation (SFIC). To address the issue of the HF channel time-variation, an explicit adaptive channel estimator is used to determine the unknown channel coefficients. In addition, we have also proposed a hybrid ACE TEQ algorithm. Numerical results show that the ACE-SFIC-based TEQ scheme is the best in terms of trade-off between bit-error rate (BER) and implementation complexity for the STANAG 4285 military waveforms.

Bit-error rate (BER) expressions of a suboptimum maximum-likelihood (ML) receiver with the composite effect of partial-band noise jamming and multitone jamming are derived for fast frequency-hopped systems employing M-ary frequency-shift-keying modulation over Rician-fading channels. These BER expressions can be used to study the system performance under Rayleigh fading as a special case. Owing to the fact that the computation of the logarithm of the modified Bessel function is non-linear in nature, one of the existing approximations is required to derive the BER expressions for the analysed system. A suboptimum ML receiver structure is therefore proposed and analysed. The analytical results are compared with simulation results. Under various jamming and fading conditions, the proposed suboptimum ML receiver is found to be able to suppress interference effectively.

In this study, the performance of a synchronous fast frequency-hopped multiple-access (MA) M-ary frequency-shift-keying system employing maximum-likelihood (ML) method over either frequency-selective Rician- or Rayleigh-fading channels is investigated. The ML receiver structures are derived and analysed. It is assumed that all the signals arrive at a receiver with the same power strength and all the users operating in the system undergo independent frequency-selective fading. The performance of the ML receivers is compared with that of the linear-combining and the product-combining receivers. The bit-error rate results of the two conventional receivers are obtained via simulation. The proposed analysis, validated by simulation results, shows that the proposed ML receivers can suppress the MA interference more effectively than other existing receivers under different fading conditions. Moreover, the proposed ML receivers are shown to be robust against the inaccuracy in estimation of the required side information.

Bit-error rate (BER) expressions of generalised selection combining with low-density parity-check (LDPC) codes, using binary phase-shift keying signals, over an independent and identically distributed Rayleigh-fading channel are derived using the Gaussian approximation (GA) approach. BER results for both selection combining and maximum-ratio combining can be computed from this BER expression as special cases. The symmetry and stability conditions of both density evolution (DE) and GA analysis are also studied. The degree distribution for irregular LDPC codes is optimised using differential evolution. The theoretical results are compared with both simulation results and DE thresholds. These BER expressions allow us to achieve a significant reduction in computational complexity for analysing the system performance as compared to simulation and DE.

The two wave with diffused power (TWDP) fading model is a very useful fading model characterised by two specular waves in the presence of other diffused waves and is applicable to both the Rayleigh and Rician fading channels as special cases. The performance of switch diversity with binary modulation schemes over the TWDP fading channel is examined. The four types of switch diversity investigated in this study comprise of the switch-and-stay combining, switch-and-examine combining, switch-and-examine combining with post-selection and scan-and-wait combining. The expressions of the average output signal-to-noise ratio (SNR) at the receiver and bit-error rate (BER) are derived and presented. The pre-determined SNR thresholds of the switch diversity over the TWDP fading channel are optimised to obtain the minimum BER. Analytical results are validated by simulation.

In this paper, we propose a joint iterative detection/decoding scheme for a generalized discrete two-dimensional (2D) interference channel with low-density parity-check (LDPC) codes. A reduced-state form of the channel detector is also proposed to further reduce the system complexity. To achieve better performance, iterations are introduced between the two constituent channel detectors and among the two constituent detectors with the LDPC decoder. The computational complexity and performance of different iteration schemes are analyzed. Simulation results show that the proposed detection scheme can mitigate the 2D interference effectively and the LDPC codes can be well integrated to the 2D iterative detector to further improve the system performance significantly.

We propose an efficient successive relaying (SR) transmission protocol for multiple-relay cooperative systems under the half-duplex constraint. In this protocol, the process of relay selection is conducted once the instantaneous channel state information changes. During each channel coherent interval, the source keeps transmitting newly generated messages, and two selected relays successively decode and forward the source's information to the destination. In particular, in one time slot, a selected relay jointly decodes both signals transmitted from the source and the other selected relay. In the next time slot, this relay forwards the superposition of these two decoded signals. The destination jointly decodes messages at the end of each interval. The lower bound of outage probability is derived in a closed-form expression and the diversity-multiplexing trade-off (DMT) performance is characterized as well. It is demonstrated by the numerical results that the proposed SR protocol is capable of achieving both full diversity gain and high multiplexing gain.

In this paper, we propose a detection algorithm to detect unknown multitone interference (MTI) encountered in frequency-hopped spread spectrum (FH-SS) systems over a Rayleigh fading channel and additive white Gaussian noise by using autoregressive (AR) spectral estimation method. The proposed algorithm is performed in the AR coefficient domain. The incoming received data is separated into non-overlapping data segments, and the Yule-Walker (YW) AR method is applied on each data segment to obtain the AR coefficient vector. The resultant coefficient vectors are used in the averaging process to obtain the spectrum estimate of the MTI. Computer simulations are conducted in order to investigate detection performance of the proposed AR spectral averaging technique and comparisons are made between the proposed scheme and the fast Fourier transform (FFT) based scheme. Numerical results show that the proposed technique is able to detect the MTI accurately under such a channel environment even at low signal-to-noise power ratio (SNR) condition. The comparisons reveal that the proposed AR detection technique is promising to be employed in slow FH-SS systems to detect the MTI due to higher estimation accuracy and better reliability as compared to the FFT- detection technique.

Energy-efficient design has become increasingly important to battery-powered wireless devices. In this paper, we focus on the energy efficiency of a cognitive radio network, in which a secondary user senses the channels licensed to some primary users sequentially before it decides to transmit. Energy is consumed in both the channel sensing and transmission processes. The energy-efficient design calls for a careful design in the sensing-access strategies and the sensing order, with the sensing strategy specifying when to stop sensing and start transmission, the access strategy specifying the power level to be used upon transmission, and the sensing order specifying the sequence of channel sensing. Hence, the objective of this paper is to identify the sensing-access strategies and the sensing order that achieve the maximum energy efficiency. We first investigate the design when the channel sensing order is given and formulate the above design problem as a stochastic sequential decision-making problem. To solve it, we study another parametric formulation of the original problem, which rewards transmission throughput and penalizes energy consumption. Dynamic programming can be applied to identify the optimal strategy for the parametric problem. Then, by exploring the relationship between the two formulations and making use of the monotonicity property of the parametric formulation, we develop an algorithm to find the optimal sensing-access strategies for the original problem. Furthermore, we study the joint design of the channel sensing order and the sensing-access strategies. Lastly, the performance of the proposed designs is evaluated through numerical results.

A maximum-likelihood (ML) receiver structure is proposed for fast frequency-hopped M-ary frequency-shift keying communication systems over Rayleigh-fading channels with the composite effects of multitone jamming (MTJ) and partial-band noise jamming (PBNJ). The corresponding semi-analytical bit-error rate (BER) expressions of the proposed ML receiver are also presented and validated by simulation results. Numerical results show that the BER performance with both MTJ and PBNJ is bounded by the two extreme cases, where only MTJ or PBNJ is present. It is also found that the proposed ML receiver can better counteract MTJ than PBNJ.

In this paper, we investigate the diversity-multiplexing tradeoff (DMT) of a multiple-input-multiple-output (MIMO) full-duplex single-user multihop relay channel, where a pair of source and destination communicates via multiple layers of relays. All communication terminals could be equipped with multiple antennas. The relays operate in a full-duplex mode. By incorporating time-domain linear transformation into amplify-and-forward (AF) based relaying, we propose an AF-based space-time relay scheme and show that the DMT upper bound of the channel can be achieved by properly designing space-time (ST) codes at the source.

In this paper, diversity-multiplexing tradeoff (DMT) of the delay-limited symmetric two-user single-antenna fading interference channel (IFC) with source cooperation is evaluated under both full-duplex and half-duplex cooperation constraints. The interference signal and the desired signal received by each destination node are assumed to be of comparable strength. Under each cooperation constraint, DMT upper and lower bounds are derived and shown to be tight, i.e., the lower bound meets the upper bound. A full characterization of the DMT of the channel is thus established. The upper bounds are evaluated using the capacity upper bounds and the lower bounds are obtained based on our proposed transmission schemes. The proposed transmission schemes only require partial channel state information at transmitter side (CSIT), making them suitable for practical applications. Specifically, for the transmission scheme designed under the full-duplex constraint, the partial CSIT is obtained by letting each destination represent the fading magnitude of each of its incoming links using 1 bit of information and feed back this information to the sources. In the half-duplex case, the proposed transmission scheme requires no more than 3 bits of feedback information to represent the fading magnitude of each link. Our DMT results show that source cooperation can notably improve the system diversity performance over the whole multiplexing gain region even under the half-duplex constraint.

As one of the key technologies for future wireless communication systems, user cooperation has a great potential in improving the system performance. In this paper, the diversity benefit of user cooperation is evaluated using diversity-multiplexing tradeoff (DMT) as the performance metric. Ways of exploiting the diversity benefit are devised. We investigate two typical channel models, namely, the multiple-access channel (MAC) and the interference channel (IFC). For the MAC, all the terminals are equipped with multiple antennas and theK(K≥ 2) sources cooperate in a full-duplex mode. We determine the optimal DMT of the channel and propose a compressed-and-forward (CF) based cooperation scheme to achieve the optimal DMT. For the IFC, we consider a two-user channel with single-antenna terminals and full-duplex source cooperation. A DMT upper bound and two DMT lower bounds are derived. The upper bound is derived based on a channel capacity upper bound, and the lower bounds are derived using decode-and-forward (DF) based cooperation schemes. In most channel scenarios, the bounds are found to be tight. This implies that under certain channel scenarios, the optimal DMT of the channel can be achieved by DF-based cooperation schemes.

In this paper, we propose a transmission scheme for the two-user symmetric multiple antenna interference channel (IFC) and show that the proposed transmission scheme can achieve the optimal diversity-multiplexing tradeoff (DMT) of the channel. The proposed transmission scheme requires only limited channel state information at the transmitter (CSIT) and is suitable for practical implementation. The limited CSIT is obtained by letting the destinations quantize the required information and feed back to the sources. Rules for implementing the quantization are proposed and the number of bits needed to represent the quantization is calculated. It is shown that for the proposed transmission scheme to be DMT optimal, the number of feedback bits should increase in log scale with respect to signal-to-noise ratio.

Low-density parity-check (LDPC) codes combined with cascade combining are able to achieve excellent bit-error rate (BER) performance over multipath fading channels. Cascade combining, which involves two stages of diversity combining, is very useful for situations where site diversity exists and it can reduce the complexity of the combiner when the number of diversity branches increases. The average output signal-to-noise ratio and the uncoded BER expressions of cascade combining over independent and identically distributed (i.i.d.) Nakagami-m fading channels are derived. The BER expressions of cascade combining with LDPC codes over i.i.d. Nakagami-m fading channels are derived based on the Gaussian approximation (GA) approach. These expressions include selection combining and maximum-ratio combining as special cases. The signal-to-noise ratio (SNR) thresholds for error-free decoding are obtained using density evolution (DE). Comparisons among GA analysis, DE analysis, and simulations show that they are in good agreement. The expressions obtained from the GA analysis provide better theoretical understanding of the system performance and allow us to compute the BER and SNR threshold more efficiently as compared to DE and simulations. Lastly, the stability conditions for GA and DE analyses, which are found to be exactly the same, are also presented.

Abstract In this paper, we derive the upper bound of bit‐error rate (BER) performance and diversity gain for a decode‐and‐forward (DF) cooperative system. Either maximal‐ratio combining (MRC) or cooperative MRC (C‐MRC) is employed at the receiver in the presence of independent, non‐identical Nakagami‐m fading. Both analytical and simulation results show that C‐MRC takes advantage of spatial diversity more efficiently and thus achieves the same or better performance and diversity order as compared to MRC. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, we investigate the diversity-multiplexing tradeoff (DMT) of the delay-limited symmetric two-user fading interference channel (IFC) with full-duplex source cooperation. Upper and lower bounds on the channel DMT are derived and shown to be tight, i.e., the lower bound meets the upper bound. The DMT behavior of the channel is thus fully determined. The upper bound is derived based on a channel capacity upper bound. The lower bound is derived based on a proposed transmission scheme which requires only limited CSIT obtained from destination feedback. Specifically, the magnitude of each of the fading links is represented by the destinations using one bit of information and fed back to the sources. The DMT result shows that source cooperation can notably improve the system diversity performance over the whole multiplexing rate region.

In this paper, we investigate the optimal transmitter design, under the restriction of Gaussian signalling without preprocessing of information, for a secure multiple-input single-output (MISO) cognitive radio network (CRN), which consists of four terminals: a pair of secondary user transmitter (SU-Tx) and receiver, an eavesdropper and a primary user (PU). It is assumed that all the channel state information is not perfectly known at the SU-Tx due to the channel estimation errors and the loose cooperation between the SU and the PU. The design involves a nonconvex semi-infinite optimization problem, which maximizes the rate of the secondary link while avoiding harmful interference to the PU and preventing the eavesdropper from decoding the messages sent regardless of the uncertainties in the CSI. For this challenging optimization problem, we relate it with a sequence of semi-infinite capacity-achieving transmitter design problems in an auxiliary CRN without any eavesdropper, which can then be solved through transformations and using convex semidefinite programs. Finally, numerical examples are presented to evaluate the performance of the proposed algorithm.

In this study, the authors analyse the bit-error rate (BER) performance of band-limited direct-sequence code-division multiple-access (DS-CDMA) systems employing two types of multiuser detectors, namely, linear decorrelator with whitening (LDW) and linear minimum mean-squared error (MMSE) detector over frequency-selective multipath channels with multitone jamming (MTJ). The authors consider the generalised-K distribution in order to include both shadowing and small-scale fading effects. Generalised-K distribution is generic and versatile as it can incorporate various composite fading and shadowing effects observed in wireless communication channels with mathematical tractability. The authors derive analytical BER expressions that are functions of band-limited pulse shapes, MTJ parameters and shadowing and fading parameters of the wireless channel. The system incorporates either a Nyquist pulse or a cosine band-limited pulse shape. Numerical results show that the systems with cosine pulse demonstrate better BER performance than the ones with Nyquist pulse in the presence of MTJ. Furthermore, in the presence of MTJ, MMSE-based systems demonstrate improved BER performance as compared to LDW-based systems. The authors also observe that the systems employing two-dimensional scheme, that is, the combination of space and multipath diversity, outperform the ones with multipath diversity scheme.

In this study, the effects of timing and frequency offsets on bit-error rate (BER) performance of fast frequency-hopped M-ary frequency-shift keying communication systems over Rician-fading channels with both multitone jamming (MTJ) and partial-band noise jamming (PBNJ) are investigated. Analytical BER expressions are derived for both linear-combining and product-combining receivers. Numerical results show that under both MTJ and PBNJ conditions, the BER performance falls between the two extreme cases, in which either MTJ or PBNJ presents. It is found that the BER performance is severely degraded as the timing or frequency offset increases. The product-combining receiver is found to be more sensitive to the timing and frequency offsets than the linear-combining receiver. It is also observed that for the linear-combining receiver, the optimum diversity order increases as the timing and frequency offset increases over both Rician-fading and Rayleigh-fading channels; however, the reverse is true for the product-combining receiver.

In this paper, we address the physical-layer security issue of a secondary user (SU) in a spectrum-sharing cognitive radio network (CRN) from an information-theoretic perspective. Specially, we consider a secure multiple-input single-output (MISO) cognitive radio channel, where a multi-antenna SU transmitter (SU-Tx) sends confidential information to a legitimate SU receiver (SU-Rx) in the presence of an eavesdropper and on the licensed band of a primary user (PU). The secrecy capacity of the channel is characterized, which is a quasiconvex optimization problem of finding the capacity-achieving transmit covariance matrix under the joint transmit power and interference power constraints. Two numerical approaches are proposed to derive the optimal transmit covariance matrix. The first approach recasts the original quasiconvex problem into a single convex semidefinite program (SDP) by exploring its inherent convexity; while the second one explores the relationship between the secure CRN and the conventional CRN and transforms the original problem into a sequence of optimization problems associated with the conventional CRN, which helps to prove that beamforming is the optimal strategy for the secure MISO CR channel. In addition, to reduce the computational complexity, three suboptimal schemes are presented, namely, scaled secret beamforming (SSB), projected secret beamforming (PSB) and projected cognitive beamforming (PCB). Lastly, computer simulation results show that the three suboptimal schemes can approach the secrecy capacity well under certain conditions.

In this paper, we study the sensing-throughput tradeoff problem for a multiple-channel cognitive radio (CR) network. In particular, using the sensing-throughput tradeoff metric, we investigate the design of the optimal spectrum sensing time and power allocation schemes so as to maximize the aggregate ergodic throughput of the cognitive radio network to guarantee the quality of service (QoS) of the primary users (PUs) without exceeding the power limit of the secondary transmitter. The optimal sensing time and power allocation strategies are developed under the average power constraint. Finally, numerical results show that, for a CR network with 3 channels, whose signal-to-noise ratio of PUs are -12dB, -15dB and -20dB, respectively, there is an optimal sensing time, and the optimal sensing time is almost insensitive to the total transmit power.

To improve the spectrum utilization efficiency, cognitive radio (CR) has been proposed by allowing a cognitive radio network (CRN) to coexist with a licensed primary network. The security issues, although critical, have been less explored in the literature of CRN. In this paper, we consider a secure CRN in which a multi-antenna secondary user (SU) transmitter sends confidential information to a SU receiver on the same frequency band with a primary user (PU) in the presence of an eavesdropper. All receive terminals are equipped with a single antenna. The capacity-achieving transmitter design is formulated as a quasiconvex optimization problem to maximize the rate of the secondary link while avoiding harmful interference to the PU and preventing the eavesdropper from decoding the messages sent. By exploring the inherent convexity, the original problem is solved efficiently by a single semidefinite program (SDP). Besides, two suboptimal algorithms are proposed to reduce the computational complexity, namely, scaled secret beamforming (SSB) and projected secret beamforming (PSB). It is shown through computer simulations that the two suboptimal algorithms can achieve close-to-optimal secrecy capacity under certain conditions.

The authors studied bit-error rate (BER) performance of asynchronous band-limited direct-sequence code-division multiple-access (DS-CDMA) systems with various diversity-combining receivers over Generalised-K fading channels. The effects of band-limited pulse shapes, multitone jamming, multiple-access interference as well as both flat and frequency-selective fading are considered. The Generalised-K model is adopted in order to include the effects of shadowing and fading of a wireless channel. The authors consider binary phase-shift keying as the modulation technique. The analytical expressions are valid for any arbitrary value of Generalised-K distribution parameters. Two types of band-limited pulses, namely spectrum raised cosine and Beaulieu–Tan–Damen (BTD) pulses, are incorporated in the analysis. Numerical results show that the system with BTD pulse outperforms the one with SRC pulse for various diversity-combining receivers under various channel conditions. Furthermore, by incorporating a minimum mean-square error stage in the multipath diversity receiver, the BER performance can be further improved.

A binned dirty-paper code (DPC) divides a set of codewords into a number of bins. The codeword in the bin that has the maximum correlation with the side information is selected as the transmitted dirty-paper codeword. This letter derives and verifies the analytical bit-error rate (BER) expression of binned orthogonal block code used as DPC in watermarking applications. The BER trends of such orthogonal DPC under constant code length or constant code rate constrains are analyzed. Finally, we propose a new class of DPC based on binned bi-orthogonal codes and demonstrate its BER performance gain over orthogonal DPC.

An optimum maximum-likelihood (ML) receiver structure for a fast frequency-hopped M-ary frequency-shift keying system over frequency-selective Rician-fading channels against partial-band-noise jamming and additive white Gaussian noise is proposed. In addition, we propose two suboptimum ML receivers and derive their corresponding analytical bit-error rate expressions.

In this paper, we consider a wideband cognitive radio network (CRN) which can simultaneously sense multiple narrowband channels and thus aggregate the perceived available channels for transmission. We study the problem of designing the optimal spectrum sensing time and power allocation schemes so as to maximize the average achievable throughput of the CRN subject to the constraints of probability of detection and the total transmit power. The optimal sensing time and power allocation strategies are developed under two different total power constraints, namely, instantaneous power constraint and average power constraint. Finally, numerical results show that, under both cases, for a CRN with three 6 MHz channels, if the frame duration is 100 ms and the target probability of detection is 90% for the worst case signal-to-noise ratio of primary users being -12 dB, -15 dB and -20 dB, respectively, the optimal sensing time is around 6 ms and it is almost insensitive to the total transmit power.

Abstract In this paper, we propose a receiver structure for transmitted‐reference ultra‐wideband (TR‐‐UWB) systems with both narrowband interference (NBI) and inter‐pulse interference (IPI) mitigation capabilities. The effects of additive white Gaussian noise (AWGN) and the IEEE 802.15.4a fading channel are also taken into consideration. We adopt band‐stop filtering to suppress the NBI. For IPI, it is statistically removed by a sum‐and‐average process. Theoretical analysis is carried out to study the lower bound of the bit‐error rate (BER) performance of the proposed receiver. Numerical results show that the proposed receiver is able to provide satisfactory performance and is robust to variations in the system design parameters. It is also observed that the proposed receiver is able to deliver good performance even when there is zero delay between the reference and data pulses, which can effectively double the system throughput. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper, we propose a noncoherent space-frequency (SF) code for multiple-input-multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems for broadband wireless communications. The proposed noncoherent SF code matrix is constructed as a combination of a noncoherent SF code matrix and a differential modulation matrix. Comparing to noncoherent SF codes and differential SF codes in the literature, the advantages of our proposed code are higher spectrum efficiency, no error floor and more suitable for broadband communication systems. Taking advantage of the codeword structure of the proposed SF code, we devise a two-stage decoding scheme, in which the decoding process is implemented in two steps by decoding the component noncoherent codeword matrix and the component differential codeword matrix sequentially. Accordingly, the decoding scheme efficiently reduces decoding complexity. Simulation results show that our proposed scheme with two-stage decoding yields better performance than the noncoherent SF codes and frequency-domain differential codes proposed in the literature.

In this paper, we focus on noncoherent space-frequency (SF) coded multiple-input-multiple-output orthogonal-frequency-division-multiplexing (MIMO-OFDM) systems. Based on OFDM subcarrier grouping, a group-based unitary space- frequency code is proposed and the effect of grouping on system performance is studied. Comparing to the coding scheme without grouping, which implements SF coding among all the OFDM tones, the proposed group-based coding scheme can greatly reduce the decoding complexity, making the noncoherent SF codes more applicable to practical use. By relating the noncoherent SF codes with packings in Grassmann manifold, we propose an efficient decoding method by restricting the implementation of decoding within a subset of the codebook. Numerical results are presented to demonstrate and verify our proposals.

Analytical expressions of bit-error rate (BER) are derived for a fast-frequency-hopping M-ary frequency-shift- keying (FFH/MFSK) spread-spectrum communication system over frequency-selective Rayleigh-fading channels with multitone jamming (MTJ) and additive white Gaussian noise. The FFH/MFSK systems employing a linear-combining receiver (LCR) and a product-combining receiver (PCR) are studied. The desired signal and MTJ are assumed to undergo independent fading. The characteristic function approach is used to derive the analytical BER expressions for higher diversity levels. The analytical BER expressions are validated by simulation results and the PCR is found to outperform the LCR when the jamming power is relatively strong.

Based on the refinement-only fast subspace tracking (RO-FST) algorithm to adaptively estimate the signal sub-space, a blind adaptive SVD-based minimum-mean-square-error (MMSE) multiuser detector is proposed in this paper for asynchronous direct-sequence code-division-multiple-access (DS-CDMA) systems over multipath fading channels. Numerical results show that the proposed detector gives low computational complexity and good performance in terms of signal-to-interference-plus-noise ratio (SINR) and bit-error-rate (BER). In addition, we apply the perturbation analysis of the proposed adaptive detector to derive the closed-form expressions for the mean-square error (MSE) and SINR. The analytical results are shown to match well with the simulation results.

In this contribution, we consider iterative multiuser detection over coded code-division multiple-access (CDMA) channels from a combinatorial optimization viewpoint and propose a low-complexity soft-input/soft-output (SISO) multiuser detector based on the k-opt local search (LS) algorithm, which was previously used for solving the traveling salesperson problem (TSP). Simulation results and complexity analysis show that the proposed detector can approach closely the performance of the full-complexity a posteriori probability (APP) multiuser detector over highly correlated convolutionally coded channels.

In this paper, an adaptive window length estimation for channel estimation in direct-sequence (DS) code-division multiple-access (CDMA) receivers is presented. The estimated optimum window length is derived based on autocovariance analysis of the estimated channel coefficients. As the propagation channel changes over time, an adaptive algorithm for updating the window length is proposed through Doppler and signal-to-noise ratio (SNR) estimations. The proposed system improves the performance by adaptively selecting and continuously updating the window lengths over a wide-range of velocities (5 to 400 kmph).

Based on the Fourier-Bessel series and exponential characteristic function approach, the paper presents analytical bit-error-rate expressions for synchronous fast frequency-hopped spread-spectrum multiple-access systems over Rician fading channels with M-ary frequency-shift-keying modulation. Linear-combining, product-combining and clipper receivers are studied. Numerical results show that both the clipper and product-combining receivers perform significantly better than the linear-combining receiver. The clipper receiver with an optimum threshold level slightly outperforms the product-combining receiver. However, the product-combining receiver is the preferred diversity-combining method because it is completely nonparametric. In addition, the optimum diversity levels for various diversity-combining receivers over Rayleigh fading channels are higher than that of the Rician fading channels.

We propose a blind user identification detection (UID) scheme based on linear prediction algorithm for asynchronous direct-sequence code-division multiple-access systems over multipath fading channels. Numerical results show that both the false alarm rate and bit error rate of the proposed algorithm are better than those of the existing subspace-based UID algorithms.

In this paper, we present analytical bit-error probability expressions of an asynchronous fast frequency-hopped multiple-access system over fading channels with multiple-access interference modeled as alpha-stable noise. Various diversity-combining receivers over both Rician fading and Rayleigh fading channels are analyzed based on the Fourier-Bessel series. Numerical results under various environments show that the two non-linear diversity-combining methods significantly outperform the linear-combining receiver

The conventional multiuser detector (MUD) based on the a posteriori probability (APP) algorithm has an exponential computational complexity in terms of the number of users. In this paper, we propose a low-complexity iterative multiuser receiver for synchronous turbo-coded code-division multiple-access (CDMA) systems. The proposed receiver is based on the Chase decoding algorithm that was previously used to decode turbo product codes. Simulation results show that the proposed receiver can significantly reduce the computational complexity with slight performance degradation compared with the APP MUD over highly correlated channels. Moreover, in this paper, we develop a numerical approach to analyze the convergence behavior of iteratively decoded CDMA channels based on density evolution technique. Analytical results are presented and shown to provide a reasonable match with what is observed in simulation.

Analytical bit-error-rate (BER) expressions are derived for various fast frequency-hopped (FFH) M-ary frequency-shift-keying receivers with the worst-case multitone jamming and additive white Gaussian noise. The BER results for different receivers are compared and the effects of the optimum diversity level on BER performance are also presented.

The conventional maximum a posteriori receiver for coded code-division multiple-access (CDMA) systems has exponential computational complexity in terms of the number of users and the memory of the channel code. In this letter, we propose a low-complexity soft-input soft-output (SISO) multiuser detector based on the reduced-state a posteriori probability algorithm. Per-survivor processing and soft interference cancellation are used to remove the residual past and future interference in the branch metric computation. The complexity of the proposed receiver is related to the reduced memory of the CDMA channel and can be adjusted according to the complexity/performance tradeoff. Simulation results show that for asynchronous convolutionally coded systems, the proposed receiver can achieve the near-single-user performance for moderate to high signal-to-noise ratios.

The convergence rate of an adaptive filter is one of the key elements which determines the performance of the filter in a moderately slow time-varying channel. In this paper a new blind minimum mean-square error (MMSE) linear detector based on the modified stochastic gradient descent (SGD) algorithm is presented. The proposed detector is simple, robust and has a faster convergence rate than the conventional SGD algorithm.

We propose iterative multiuser detectors for asynchronous code-division multiple-access with parallel-concatenated convolutional codes (turbo codes) and with serially concatenated convolutional codes (SCCC). At each iteration we update and exchange the extrinsic information from the multiuser detector and channel decoders and regenerate soft information between constituent convolutional decoders. Simulation results show that with the proposed structure, near-single-user performance can be achieved. We also propose two reduced-complexity techniques, i.e., the reduced-state iterative multiuser detector based on the T-MAP algorithm and the iterative interference canceler based on a noise-whitening filter. Simulation results show a small performance degradation for these two techniques, particularly for the T-MAP receiver.

We derive the analytical bit-error rate (BER) expressions for a fast frequency-hopped binary frequency-shift keying self-normalizing receiver over a fading channel with the worst-case band multitone jamming (MTJ) and additive white Gaussian noise (AWGN). The desired signal and MTJ are assumed to undergo independent Rician fading and our analyses, validated with simulation results, show that the system performance is not sensitive to different types of MTJ fading conditions. The self-normalizing receiver is found to be superior to the linear-combining receiver when the signal amplitude does not experience severe fading, while the converse is true under Rayleigh fading signal conditions. Under a Rician fading channel and AWGN conditions, the worst-case MTJ and the worst-case partial-band noise jamming are shown to have similar effects on the BER performance of the self-normalizing receiver with diversity.

This paper studies the bit-error rate (BER) performance of a fast frequency-hopped (FFH) binary frequency-shift-keying (BFSK) clipper receiver in the presence of multitone jamming (MTJ) and additive white Gaussian noise (AWGN). By using the Taylor-series expansion and the quantization approach, the BER expressions for higher diversity levels can be obtained without much extra computational complexity. The analytical BER results, validated by simulations, show that there is an optimum diversity level for the clipper receiver. Performance comparisons among various receivers demonstrate that the BER performance of the clipper receiver is significantly better than that of the linear-combining receiver. In addition, the clipper receiver also outperforms the product-combining receiver and the self-normalizing receiver provided that the clipping threshold is set at the desired signal power level.

We study the bit-error rate performance of a fast frequency-hopped binary frequency-shift-keying (FFH/BFSK) spread spectrum (SS) communication system over fading channels with the worst-case band multitone jamming (MTJ) and additive white Gaussian noise (AWGN). The FFH system employing a clipper receiver is investigated and the corresponding bit-error expressions are obtained using the quantization approach. The desired signal and MTJ are assumed to undergo independent fading and our analysis, validated with simulation results, shows that the performance of the system is not sensitive to a particular type of MTJ fading model.

We derive the optimum structure of a maximum-likelihood (ML) receiver for a fast frequency-hopped binary frequency-shift-keying (FFH/BFSK) spread-spectrum (SS) communication system operating in the presence of multitone jamming (MTJ) and additive white Gaussian noise (AWGN). It is shown that the side information of noise variance, signal tone amplitude, and multiple interfering tone amplitude at each hop, as well as the computation of nonlinear modified Bessel function are required to implement the optimum ML receiver. We have also derived and analyzed two suboptimum receivers-namely, the ML-I and ML-II receivers-for large and small signal-to-noise ratio (SNR), respectively. Performance comparisons among various receivers show that the ML receiver gives the best performance, while the ML-I and ML-II receivers also outperform the other existing methods under both high and low SNR conditions.

Analytical expressions for bit-error probability are derived for a fast frequency-hopping binary frequency-shift keying (FFH/BFSK) spread-spectrum communication system over a fading channel with worst-case band multitone jamming (MTJ) and additive white Gaussian noise (AWGN). An FFH system employing either a linear-combining receiver or a clipper receiver is investigated. The desired signal and MTJ are assumed to undergo independent fading, and our analysis, validated with simulation results, shows that the performance of the system is slightly improved as the severity of the MTJ fading is increased. The clipper receiver is found to be superior to the linear-combining receiver when the jamming power is strong. The worst-case MTJ is shown to be more harmful than the corresponding worst-case partial-band noise jamming over a fading channel with AWGN.