Federated Dropout is an efficient technique to overcome both communication and computation bottlenecks for deploying federated learning at the network edge. In each training round, an edge device only needs to update and transmit a sub-model, which is generated by the typical method of dropout in deep learning, and thus effectively reduces the per-round latency. \textcolor{blue}{However, the theoretical convergence analysis for Federated Dropout is still lacking in the literature, particularly regarding the quantitative influence of dropout rate on convergence}. To address this issue, by using the Taylor expansion method, we mathematically show that the gradient variance increases with a scaling factor of $γ/(1-γ)$, with $γ\in [0, θ)$ denoting the dropout rate and $θ$ being the maximum dropout rate ensuring the loss function reduction. Based on the above approximation, we provide the convergence analysis for Federated Dropout. Specifically, it is shown that a larger dropout rate of each device leads to a slower convergence rate. This provides a theoretical foundation for reducing the convergence latency by making a tradeoff between the per-round latency and the overall rounds till convergence. Moreover, a low-complexity algorithm is proposed to jointly optimize the dropout rate and the bandwidth allocation for minimizing the loss function in all rounds under a given per-round latency and limited network resources. Finally, numerical results are provided to verify the effectiveness of the proposed algorithm.

Federated dropout on the weight is an efficient technique to overcome both communication and computation bottlenecks for deploying federated learning at the network edge. However, the theoretical analysis for Federated Dropout is still lacking in the literature, due to the challenge arising from the gradient bias. To address this issue, by using the Taylor expansion method, we mathematically show that the gradient vector with dropout can be approximated as an unbiased estimation of that without dropout; while its gradient variance increases with a scaling factor of γ/(1 − γ), with γ ∈ [0,θ) denoting the dropout rate and θ being the maximum dropout rate ensuring the loss function reduction. Based on the above approximation, we provide the loss function analysis for Federated Dropout. Specifically, it is shown that a larger dropout rate of each device leads to a slower convergence rate. Finally, numerical results are provided to verify the effects of dropout rate on convergence in both underfitting and overfitting scenarios.

In this paper, we consider a two-way wiretap channel in the presence of Multi-Input Multi-Output Multi-antenna Eve (MIMOME), where both nodes (Alice and Bob) transmit and receive in an in-band full-duplex manner and Eve tries to decode the information exchanged between Alice and Bob. For this system with keyless security, we provide artificial noise (AN) based signal design while assuming AN to be known/unknown at the receivers (Alice and Bob). Power allocation problems are formulated with the objective of maximization of sum secrecy rates subject to the transmit power constraint. Accounting for non-ideal self-interference cancellation, a successive convex approximation-based algorithm for the solution for the cases of full CSI, and limited CSI knowledge, including partial information at Eve. For the limited CSI case, numerical ergodic rates are optimized. Simulation results show that with power constraints satisfied, secrecy rates are maximized, and with only partial information at Eve, secrecy rates are improved accordingly.

Orthogonal time frequency space (OTFS) modulation has attracted significant attention recently due to its advantages over orthogonal frequency division multiplexing (OFDM) in high-mobility scenarios. The low-complexity transceiver design is of great significance for OTFS systems. In this paper, we propose time domain-based channel estimation and data detection methods for both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems. In the proposed method, the data is mapped in the delay-time domain as compared to the delay-Doppler domain in OTFS. By doing this, a few pilots are required to estimate the channel coefficients, and data detection is performed symbol by symbol. Simulation results show the robustness of the proposed method for different Doppler shifts and baseband modulation as compared to a single-tap zero forcing equalizer and message-passing algorithm.

With the increasing number of applications of Internet of Things (IoT) devices, co-channel interference is unavoidable among coexisting wireless networks, where multiple IoT devices transmit their observations to their respective destinations [access points (APs)]. In this scenario, we present a joint precoding and power allocation solution to minimize the mean squared error (MSE), while satisfying power constraints at individual IoT devices. In this regard, first, the necessary feasibility condition for the joint convexity of the optimization problem is derived, ensuring the global optimum solution. Subsequently, based on the solution, an iterative MSE algorithm is formulated and analyzed for convergence. The expressions for the MSE-based precoder is obtained via solving Karush–Kuhn–Tucker (KKT) conditions. Further analysis shows that the total resulting MSE at APs is limited by the observation signal-to-noise-ratio (SNR). It leads to the inference that in order to avoid the MSE saturation at APs at higher SNRs, the transmit power at IoT devices should be scaled proportional to and less than the observation SNR. Next, we compare the performance of our solution with two classical methods, namely, the minimum variance distortionless precoding (MVDP) and interference alignment (IA) methods, which are modified and enhanced for the given system. Simulations verify the above inference, and the global convergence of the MSE algorithm, with robustness to initializations yielding the better precoders and power allocation as compared to MVDP’s and IA’s in terms of the averaged total MSE performance.

Stacked intelligent metasurfaces (SIM) is a revolutionary technology, which can outperform its single-layer counterparts by performing advanced signal processing relying on wave propagation. In this work, we exploit SIM to enable transmit precoding and receiver combining in holographic multiple-input multiple-output (HMIMO) communications, and we study the achievable rate by formulating a joint optimization problem of the SIM phase shifts at both sides of the transceiver and the covariance matrix of the transmitted signal. Notably, we propose its solution by means of an iterative optimization algorithm that relies on the projected gradient method, and accounts for all optimization parameters simultaneously. We also obtain the step size guaranteeing the convergence of the proposed algorithm. Simulation results provide fundamental insights such the performance improvements compared to the single-RIS counterpart and conventional MIMO system. Remarkably, the proposed algorithm results in the same achievable rate as the alternating optimization (AO) benchmark but with a less number of iterations.

Designing an efficient receiver for multiple users transmitting orthogonal frequency-division multiplexing signals to the base station remain a challenging interference-limited problem in 5G-new radio (5G-NR) system. This can lead to stagnation of decoding performance at higher signal-to-noise-and-interference regimes. Further, the problem is exacerbated in future critical internet-of-thing (IoT) devices operating on smaller block size due to latency constraints and IoT users moving at varying speeds introducing Doppler shift and delay spread. In this work, we propose a novel deep learning (DL)-based U-net- and Resnet-inspired receiver for multi-user uplink transmission for a 5G-NR system that replaces only the signal demapping block of the receiver chain. Compared to traditional U-net frameworks, we propose a DL receiver with upsampling in the encoder that takes complex equalized symbols as input and downsampling in the decoder to output bit-wise log-likelihood ratios for multiple users. Further, residual skip connections are introduced in the decoder to facilitate stronger connections to the upsampling blocks. Finally, the DL receiver is optimized by maximizing the optimal bit-metric decoding rate. Comparative simulations show that our proposed DL receiver outperforms traditional 5G-NR receivers by considerable margins.

In this paper, we study the benefits of in-band full-duplex (IBFD) and multi-input multi-output (MIMO) systems on the physical layer-based secret key generation (PHY-SKG) scheme. The secret key capacity (SKC) of a channel frequency response (CFR)-based PHY-SKG scheme in IBFD-MIMO systems is derived with practical imperfections and compared to its half-duplex (HD) counterpart. The results demonstrate that IBFD benefits the SKC over HD in two aspects: 1) simultaneous measurements; 2) more resources for probing to reduce errors. However, the benefits are compromised by the overheads and imperfections of self-interference cancellation (SIC). MIMO systems can significantly improve the SKC, while enlarged antenna arrays result in increased probing errors. Besides, longer overheads will be required to implement effective SIC, decreasing the IBFD gain over HD. 3GPP specification-based simulations verify the theoretical analysis.

In beyond fifth-generation and sixth-generation, integrated sensing and communications (ISAC) will benefit many aspects, especially for vehicle-to-everything (V2X) communications. However, the high mobility feature of the moving vehicles distorts the performance of the well-known orthogonal frequency division multiplexing (OFDM) modulation, which encourages the emergence of the orthogonal time frequency space (OTFS) modulation. Adopting the subarray-based hybrid beamforming, by leveraging the advantage of the strong line-of-sight link given by the air-ground channel, we design an unmanned aerial vehicle (UAV) supported in-band-full-duplex (IBFD)-OTFS-ISAC system operating in the frequency range 2 band for V2X communications, where the motion parameters are tracked by the maximum log-likelihood (ML) estimator. Simulation shows that the ML estimator can satisfactorily track the vehicles with similar accuracy under both OFDM and OTFS-based IBFD-ISAC systems. OTFS modulation outperforms the OFDM regarding spectral efficiency due to less cyclic prefix overhead paid.

Hearing loss is among the most serious public health problems, affecting as much as 20% of the worldwide population. Even cutting-edge multi-channel audio-only speech enhancement (SE) algorithms used in modern hearing aids face significant hurdles since they typically magnify noises while failing to boost speech understanding in crowded social environments. Recently, for the first time we proposed a novel integration of 5G cloud-radio access network, internet of things (IoT), and strong privacy algorithms to develop 5G IoT enabled hearing aid (HA) [1]. In this demonstration, we show the first-ever transceiver (PHY layer) model for cloud-based audio-visual (AV) SE, which meets the requirements for high data rate and low latency of forthcoming multi-modal HAs (such as Google glasses with integrated HAs). Even in highly noisy conditions like cafés, clubs, conferences, meetings, etc., the transceiver [2] transmits raw AV information from a hearing aid system to a cloud-based platform and obtains a clear signal. In Fig. 1, we illustrate an example of our cloud-based AV SE hearing aid demonstration. Herein, the left-side computer and Universal Software Radio Peripheral (USRP) x310 function as IoT systems (hearing aids), the right-side USRP serves as an access point or base station, and the right-side computer serves as a cloud-server for operating NN-based SE models. Please take note that the channel between the HA device and the cloud is defined as an uplink channel, whereas the channel between the access point (cloud) and the HA device is defined as a downlink channel. Given the time-varying sensitivity of the data received at HA devices, the uplink channel can therefore handle a variety of data rates. As a result, a customized long-term evolution (LTE)-based frame structure is developed for uplink transmission of data. It provides error-correction codes in the 1.4 MHz and 3 MHz bandwidths with a variety of modulations and code rates. Furthermore, the cloud access point simply supports a limited transmission rate because it only transmits audio data to the HA equipment. In order to support real-time AV SE, a modified frame structure for LTE with 1.4 MHz of bandwidth is developed. The AV SE algorithm receives cropped lip images of the target speaker and a noisy speech spectrogram, and it produces an ideal binary mask that lessens the noise-dominant regions while improving the speech-dominant areas. We use the depth-wise separable convolutions, reduced STFT window size of 32 ms, smaller STFT window shift of 8 ms, and 64 convolutions in the audio feature extraction layers of our Cochlea-Net [3] multi-modal AV SE neural network architecture to reduce processing latency. Furthermore, the visual feature extraction framework is employed. Our proposed architecture can handle streaming data frame-by-frame. Thus, the users will experience for the first time the real-world development of a physical layer transceiver that can perform AV SE in real-time under strict latency and data rate requirements. For this demonstration, we will bring two computers and two USRP x310 devices.

Physical layer-based secret key generation (PHY-SKG) schemes have attracted significant attention in recent years due to their lightweight implementation and ability to achieve information-theoretical security. In this paper, we study a channel frequency response (CFR)-based SKG scheme for in-band full-duplex (IBFD)-multi-input and multi-output (MIMO) systems. We formulate the intrinsic practical imperfections and derive their effects on the probing errors. Then we derive closed-form expressions for the secret key capacity (SKC) in the presence of a passive eavesdropper accordingly. We analyze the asymptotic behavior of the SKC in the high-SNR regime and reveal the fundamental limits for IBFD and HD probing. Based on the asymptotic SKC, we investigate the conditions under which IBFD can outperform HD. Numerical results illustrate that effective analog self-interference cancellation (ASIC) depth is the basis for IBFD probing to gain benefits over HD. Finally, we analyze the properties of the collected samples of the CFR-based SKG scheme and propose an averaging pre-processing and a segmental quantization, which reduce the key disagreement rate and remove the effects of large-scale fading to guarantee randomness. 3GPP specification-based simulations and the National Institute of Standards and Technology (NIST) test suite verify the theoretical analysis and the effectiveness of the proposed SKG scheme.

Full duplex (FD) relaying can provide double spectral efficiency. Despite advanced self-interference cancellation techniques, residual self-interference (RSI) limits the performance significantly. We present an autoencoder (AE)-based block coded modulation (BCM) and differential BCM (d-BCM) for an FD amplify-and-forward (FD-AF) relay network that can tackle the deteriorating impacts of RSI. Existing works treat AE frameworks as black-box with minimal/no focus on training convergence, limiting AE’s practical deployment. Focussing on training convergence, firstly, we show that training of AE converges above minimum signal-to-noise-ratio (SNR) and below maximum RSI level, and CSI helps in faster convergence. Secondly, we establish a relationship between training hyper-parameters and AE-based BCM/d-BCM design, by showing that, for any given hyper-parameters, training of the AE has converged to its maximum potential of decoding if AE’s encoder has designed$2^{k}$codewords, with an emphasis on the minimum required training samples. To open the black-box AE, we reveal five observations in the AE-based designed codewords concerning Euclidean distance, packing density, hamming distance, and kurtosis, that resemble the desired observations of theoretical random coded modulations. By extensive simulations, we show that the proposed AE outperforms the conventional methods considerably for varying SNR, RSI, transmission rate, channel estimation errors, and small/practical block lengths.

In this paper, we design a first of its kind transceiver (PHY layer) prototype for cloud-based audio-visual (AV) speech enhancement (SE) complying with high data rate and low latency requirements of future multimodal hearing assistive technology. The innovative design needs to meet multiple challenging constraints including up/down link communications, delay of transmission and signal processing, and real-time AV SE models processing. The transceiver includes device detection, frame detection, frequency offset estimation, and channel estimation capabilities. We develop both uplink (hearing aid to the cloud) and downlink (cloud to hearing aid) frame structures based on the data rate and latency requirements. Due to the varying nature of uplink information (audio and lip-reading), the uplink channel supports multiple data rate frame structure, while the downlink channel has a fixed data rate frame structure. In addition, we evaluate the latency of different PHY layer blocks of the transceiver for developed frame structures using LabVIEW NXG. This can be used with software defined radio (such as Universal Software Radio Peripheral) for real-time demonstration scenarios.

This paper investigates the self-interference cancellation (SIC) techniques for in-band full-duplex (IBFD) radios operating in the FR2 band (> 24.25 GHz), where large-scale antenna arrays and RF beamforming are usually leveraged. We give a detailed analysis of the effects of such architecture on RF and digital cancellations with considerations of noise and distortions from the transceiver and cancellers. The feasibility of the RF cancellation scheme with alternative architecture is analysed in terms of the number of taps, and the overall SIC performance is evaluated in terms of total residual noise caused by the self-interference. Numerical results illustrate that the RF beamforming may increase the cost of a single RF canceller, but the reduced number of cancellers due to RF beamforming still significantly reduces the total cost and complexity (i.e., more than 1000 times). The self-interference can be suppressed to the receiver noise floor with sufficient RF cancellation (> 35 dB), low noise and distortions caused by RF cancellers (10 dB lower than the receiver noise floor), and appropriate transceiver distortions (< −80 dB). Besides, more subarrays at the receiver can reduce the requirements but result in higher costs.

This paper proposes a 3GPP-inspired design of the in-band-full-duplex (IBFD) integrated access and backhaul (IAB) networks for integrated sensing and communications (ISAC) in the frequency range 2 (FR2) band for vehicle-to-everything (V2X) communications. Unlike half-duplex (HD), IBFD-IAB-nodes (i.e., roadside units) in this work are doing sensing and communications at the same time and frequency, which enhance the spectral efficiency (SE) and sensing accuracy, as well as reduce the latency. With the help of the extended Kalman filter (EKF), radar sensing is performed at the IBFD-IAB-nodes for the multi-vehicle scenario. Assuming the high power self-interference (SI) at the IBFD-IAB-node has been successfully canceled in the propagation, analog, and digital domains, only the residual SI is reserved in this work. Numerical results show that the closer the vehicle to the IAB-node, the higher the SE it can get. Compared with HD ISAC-IAB systems, our proposed IBFD ISAC-IAB systems can double the SE at the vehicle.

In this paper, a generalized superimposed training (GST) scheme is used for uplink cell-free massive multiple-input multiple-output (mMIMO) systems to mitigate the pilot contamination effect, where multiple users are served by various access points (APs). In the proposed scheme, the pilots and data sequences are superimposed entire coherence time using a novel precoding technique. We consider variable data length in the Rician fading environment and estimate the channel using the least-squares (LS) estimator, and subsequently, the data are estimated. Moreover, we derive an expression for signal-to-interference-plus-noise ratio (SINR) for the proposed GST scheme. The results are given in terms of bit error rate (BER), sum-rate, and normalized mean-squared error (NMSE) of the channel estimation. We compare our proposed GST scheme, the conventional superimposed training (ST), and the regular pilots (RP) scheme, and showed the benefit of the proposed approach. Finally, two receiver cooperation levels are considered, including fully centralized processing and localized processing. We realize lower NMSE and BER but the higher value of sum-rate in fully centralized processing with the GST scheme.

This paper proposes a generalized superimposed channel estimation scheme for an uplink cell-free massive multiple-input multiple-output (mMIMO) system, which is aided by several reconfigurable intelligent surfaces (RIS) to enhanced performance in terms of coverage and spectral efficiency. We consider that the system has both direct links (between access points (APs) and users) and indirect links through each RIS. The estimated channels are used to detect the data streams, and consequently, bit error rate (BER) and sum-rate performances are evaluated. Moreover, we optimize phase shift coefficients to minimize the channel estimation error statistics. Two levels of receiver cooperations (fully centralized processing and local processing) are considered in this work. Simulation results show that the RIS-aided cell-free mMIMO system with the optimal RIS phase coefficients can effectively improve the channel estimates as compared to those without RIS or with randomly phased RISs. It is also verified that fully centralized processing provides much lower channel estimation normalized mean-square error (NMSE) and BER than that for local processing, and confirmed that generalized superimposed training (GST) scheme shows the better performance in channel estimates compared with the standard superimposed training (ST) and the regular pilots (RP) scheme.

This paper proposes a wideband self-interference cancellation scheme for beyond 5G full-duplex communications. Especially, optical components are explored to achieve efficient wideband RF cancellation. We use a fiber array to form multiple independent tunable delay lines for a low-complexity and low-cost design. The processing and implementation details are given, and its performance is evaluated with practical concerns (e.g., inaccurate hardware measurements and tuning speed). Then, a nonlinear digital canceller is utilised to generate a replicate of the received baseband digitised self-interference signal along with the nonlinear effects induced by the power amplifier. The relationship between RF and digital cancellation is explored, and an appropriate RF cancellation amount is given based on this. Simulation results illustrate that more than 30 dB of RF cancellation can be achieved within 400 MHz bandwidth centred at 2.5 GHz, and the residual self-interference is brought to close the noise floor by the nonlinear digital canceller with practical transceiver nonlinearity and distortions.

Federated learning (FL) is an emerging distributed learning algorithm where the process of data acquisition and computation are decoupled to preserve users’ data privacy. In the training process, model weights have to be updated at both base station (BS) and local users sides. These weights, when exchanged between users and BS, are subjected to imperfections in uplink (UL) and downlink (DL) transmissions due to limited reliability of wireless channels. In this paper, for a FL algorithm in a single-cell massive MIMO cellular communication system, we investigate the impacts of both DL and UL transmissions and improve the communication-efficiency by adjusting global communication rounds, transmit power and average codeword length after quantization. Simulation results on standard MNIST dataset with both i.i.d and non-i.i.d training data distributions are also presented. Our simulation results have shown accelerated learning for various local steps and transmit power. The network energy consumption has been reduced while achieving similar testing accuracy at higher iterations.

In this paper, the problem of distributed content caching in a small-cell Base Stations (sBSs) wireless network that maximizes the cache hit performance is considered. Most of the existing works consider static demands, however, here, data at each sBS is considered to be correlated across time and sBSs. Federated learning (FL) based caching strategy is proposed which is assumed to be a weighted combination of past caching strategies of the sBS as well as the neighbouring sBSs. A high probability generalization guarantees on the performance of the proposed federated caching strategy is derived. The theoretical guarantee provides following insights on obtaining the caching strategy: (i) run regret minimization at each sBS to obtain a sequence of caching strategies across time, and (ii) maximize an estimate of the bound to obtain a set of weights for the caching strategy which depends on the discrepancy. Theoretical guarantee on the performance of the least recently frequently used (LRFU) caching strategy is derived. Further, FL based heuristic caching algorithm is also proposed. Finally, it is shown through simulations using Movie Lens dataset that the proposed algorithm significantly outperforms the recent online learning algorithms.

Regular pilots in a massive multi-input multi-output (MIMO) system with large number of users suffer from the pilot contamination effect due to limited training time. In this paper, for a cell-free massive MIMO system, we have proposed a generalized superimposed pilot (GSP) scheme, where the available number of pilots are equal to the coherence time slots, and the transmitting data symbols are spread over the coherence time with the help of simple precoding. Further, in order to keep the system scalable, a low complexity and distributed time processing approach is employed, and the corresponding rate components are analyzed. It is shown that with careful design of precoding matrix and number of data symbols, the GSP symbols can provide much better channel estimation and data detection performance, as compared to the regular pilot scheme and the conventional superimposed scheme. These results have been verified via simulations. It is also inferred that centralized processing in cell free system improves the data detection performance than localized processing. Iterative data detection at the central node also improves the MSE of data estimates. The pilot contamination effect, is significantly reduced due to availability of larger number of pilots, as compared to regular pilots transmission.

This paper develops a 3GPP-inspired design for the in- band-full-duplex (IBFD) integrated access and backhaul (IAB) networks in the frequency range 2 (FR2) band, which can enhance the spectral efficiency (SE) and coverage while reducing the latency. However, the self-interference (SI), which is usually more than 100 dB higher than the signal-of-interest, becomes the major bottleneck in developing these IBFD networks. We design and analyze a subarray-based hybrid beamforming IBFD-IAB system with the RF beamformers obtained via RF codebooks given by a modified Linde-Buzo-Gray (LBG) algorithm. The SI is canceled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain (OD)-based RF cancellation, where cancelers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error baseband receiver. Multiuser interference in the access link is canceled by zero-forcing at the IAB-node transmitter. Simulations show that under 400 MHz bandwidth, our proposed OD-based RF cancellation can achieve around 25 dB of cancellation with 100 taps. Moreover, the higher the hardware impairment and channel estimation error, the worse digital cancellation ability we can obtain.

Wireless edge caching is an important strategy to fulfill the demands in the next generation wireless systems. Recent studies have indicated that among a network of small base stations (SBSs), joint content placement improves the cache hit performance via reinforcement learning, since content requests are correlated across SBSs and files. In this paper, we investigate multi-agent reinforcement learning (MARL), and identify four scenarios for cooperation. These scenarios include full cooperation (S1), episodic cooperation (S2), distributed cooperation (S3), and independent operation (no-cooperation). MARL algorithms have been presented for each scenario. Simulations results for averaged normalized cache hits show that cooperation with one neighbor (S3) can improve the performance significantly closer to full-cooperation (S1). Scenario 2 shows the importance of frequent cooperation, when the level of cooperation is high, which depends on the number of SBSs.

The full-duplex (FD) integrated access and backhaul (IAB) technique is considered in the 3rd Generation Partnership Project (3GPP) release 16 to address the demand for high capacity, large coverage and low latency millimeter wave (mmWave) beyond 5G networks. However, the self-interference (SI) appears on the FD-IAB-node, becoming the major bottleneck in the development of these novel networks. With the assumption of successful antenna isolation, this paper proposes an SI cancellation (SIC) technique for the wideband mmWave-FD-IAB multiuser networks with the cost-efficient subarray hybrid precoding structure. The fiber Bragg grating-based analog canceler is established between the RF chain pairs of the FD-IAB-node, and the minimum mean square error baseband combiner is used at the FD-IAB-node receiver to cancel the residual SI digitally. Further, hardware impairment (HWI) is considered to capture the transceiver distortion. Simulation results show that the proposed FD-IAB network capacity is almost doubled compared to the half-duplex-IAB system when the effect of HWI is low.

The fifth generation wireless systems are starting to exploit the large bandwidths available in the millimeter-wave (mmWave) spectrum to provide high data rates. The exploitation of mmWave requires the use of compact antenna arrays with hundreds of antenna elements, which leads to very directional beam patterns. The beams at both the transmitter and the receiver are trained periodically to maintain accurate beam alignments. The trade-off between the training overhead and the achievable data rate must be considered. In this paper, we propose an adaptive beam training algorithm using deep reinforcement learning for tracking dynamic mmWave channels. Based on the patterns learnt from historical data, the proposed algorithm can sense the changes in the environment and switch between different beam training methods so that a high data rate can be achieved with a minimum amount of beam training.

The caching of popular contents in a cellular network is known to reduce the data load in the backhaul link, and have been an active area of research. This paper considers the problem of efficient distributed content coded caching in a small-cell Base Station (sBS) wireless network to improve the cache hit performance. The demands at each sBS across time and sBSs is assumed to be correlated, and is unknown. A new weighted (across time and sBS) caching strategy is proposed. A high probability lower bound on the cache hit is derived, which is obtained using the proposed strategy as a function of the cache hit of the optimal caching strategy. The bound is shown to depend on (i) the weighted average of cache hits, (ii) regret, and (iii) the discrepancy across time and sBSs (a measure of correlation of demands across time and sBSs). This provides the following insight on obtaining the caching strategy: (i) find a sequence of caching strategies by running regret minimization across time at each sBS, and (ii) maximize an estimate of the bound to obtain a set of weights. The insight is shown to result in an iterative distributed algorithm to obtain caching strategies at each sBS. The performance of the proposed caching strategy is shown to outperform Least Recently Frequently Used (LRFU) algorithm by a large margin.

Integrated Access and Backhaul (IAB) systems, millimeter-wave (mmWave), and full-duplex (FD) are the critical technologies for the 5G and beyond cellular networks. The capacity and efficiency are significantly enhanced, thanks to the large available bandwidth and simultaneous transmission. However, self-interference (SI) becomes significant, which needs to be canceled in different stages. In this paper, under the mmWave-FD-IAB systems, we propose a fast hybrid precoding algorithm using the Nyström method for the wideband single-user scenario. SI and residual SI (RSI) is canceled by RF precoder and minimum mean squared error combiner at the IAB-node transmitter and receiver, respectively. RF insertion loss with different kinds of phase shifters (PSs) and channel estimation error are considered for accounting the impact of the RF components impairment and channel uncertainty. Simulations show that the proposed design can enhance the backhaul link spectral efficiency and cancel the SI efficiently at the IAB-node. Moreover, passive PSs can tolerate more RSI than active PSs.

Abstract Hybrid processing in millimeter wave (mmWave) communication has been proposed as a solution to reduce the cost and energy consumption by reducing the number of radio‐frequency (RF) chains. However, the impact of the inevitable residual transceiver hardware impairments (RTHIs), including the residual additive transceiver hardware impairments (RATHIs) and the amplified thermal noise (ATN), has not been sufficiently studied in mmWave hybrid processing. In this work, the hybrid precoder and combiner are designed, which include both digital and analog processing by taking into account the RATHIs and the ATN. In particular, a thorough study is provided to shed light on the degradation of the spectral efficiency (SE) of the practical system. The outcomes show the steady degradation of the performance by the ATN across all SNR values, which becomes increasingly critical for higher values of its variance. Furthermore, it is shown that RATHIs result in degradation of the system only in the high SNR regime. Hence, their impact in mmWave system operating at low SNRs might be negligible. Moreover, an increase concerning the number of streams differentiates the impact between the transmit and receive RATHIs with the latter having a more severe effect.

Caching popular contents in advance is an important technique to achieve low latency and reduced backhaul congestion in future wireless communication systems. In this article, a multi-cell massive multi-input-multi-output system is considered, where locations of base stations are distributed as a Poisson point process. Assuming probabilistic caching, average success probability (ASP) of the system is derived for a known content popularity (CP) profile, which in practice is time-varying and unknown in advance. Further, modeling CP variations across time as a Markov process, reinforcement Q-learning is employed to learn the optimal content placement strategy to optimize the long-term-discounted ASP and average cache refresh rate. In the Q-learning, the number of Q-updates are large and proportional to the number of states and actions. To reduce the space complexity and update requirements towards scalable Q-learning, two novel (linear and non-linear) function approximations-based Q-learning approaches are proposed, where only a constant (4 and 3 respectively) number of variables need updation, irrespective of the number of states and actions. Convergence of these approximation-based approaches are analyzed. Simulations verify that these approaches converge and successfully learn the similar best content placement, which shows the successful applicability and scalability of the proposed approximated Q-learning schemes.

To alleviate the backhaul congestion in future hybrid heterogenous networks, this paper investigates the potential benefits of implementing storages in small base stations (SBSs) operating at frequency range 2 (FR2) bands that co-exist with a tier of massive multiple input multiple output (MIMO) macro BSs (MBSs) operating at frequency range 1 (FR1) bands. We develop a unified analytical framework and derive theoretical bounds for such a cache-enabled FR1-FR2 hybrid network under limited backhaul scenario to analyze the exact and approximate latency, average success probability of file delivery, and average data rate considering two open-access user association policies: i) location-based and ii) content-based association. Numerical results demonstrate that wireless edge caching (WEC) can improve the performance of hybrid wireless networks, albeit certain trade-offs, e.g., increasing cache-enabled SBSs cannot always improve the network performance and there exists an optimal SBS density that provides the best latency and throughput performance. Furthermore, we compare the performance of the network with respect to other key network design parameters such as cache size, content popularity, backhaul capacity, and blockages for both the user associations. Our results show that latency under content-based user association is less than that of location-based user association, and although the difference in the average rates under the two user associations is not obvious, content-based association can extricate more backhaul capacity and thus reduce installation cost significantly.

Large number of redundant requests in wireless networks have led to the hybrid satellite-terrestrial networks, where a satellite is used for content placement at edge caches at the base stations (BSs), thereby reducing backhaul link usage. In this paper, we consider in-network caching where an unavailable content at one BS can be fetched from the nearest BS in the network, before requesting from the content server. Obtaining optimal placement incurs exponentially huge computational overhead. Recent caching solutions are not scalable for large size of content library. Therefore, we propose a low-complexity approach using an action-coded deep deterministic policy gradient (AC-DDPG) algorithm towards optimizing the long-term average network delay. The proposed approach employs continuous valued popularity profiles rather than a fixed finite set in the literature. Simulation results demonstrate the successful application of proposed approach and the improvement over the most-popular content caching method.

In fifth generation (5G) wireless systems, millimetre wave (mmWave) frequency bands will be exploited to support high data demands. The exploitation of mmWave carrier frequencies allows the use of large-scale antenna arrays for three-directional beamforming. To utilise the beamforming gain, the transmitter and the receiver are required to perform beam training periodically to maintain reliable connectivity. This brings an inevitable training overhead for beam measurements. In this paper, an efficient beam training strategy is proposed and the trade-off between the data throughput and the training overhead is investigated for dynamic mmWave channels including blockage effects. By utilising the sparse nature of mmWave channels and the spatial consistency feature of realistic channels, only a limited number of beams are stored and searched based on the recent history of beam selection results. Simulation results show that the proposed beam training strategy can significantly reduce the training overhead while achieving comparable data throughput to the exhaustive beam search.

Caching popular contents in advance is an important technique to achieve low latency and reduce the backhaul costs in future wireless communications. Considering a network with base stations distributed as a Poisson point process, optimal content placement caching probabilities are obtained to maximize the average success probability (ASP) for a known content popularity (CP) profile, which in practice is time-varying and unknown in advance. In this paper, we first propose two online prediction (OP) methods for forecasting CP viz., popularity prediction model (PPM) and Grassmannian prediction model (GPM), where the unconstrained coefficients for linear prediction are obtained by solving constrained non-negative least squares. To reduce the higher computational complexity per online round, two online learning (OL) approaches viz., weighted-follow-the-leader and weighted-follow-the-regularized-leader are proposed, inspired by the OP models. In OP, ASP difference (i.e, the gap between the ASP achieved by prediction and that by known content popularity) is bounded, while in OL, sub-linear MSE regret and linear ASP regret bounds are obtained. With MovieLens dataset, simulations verify that OP methods are better for MSE and ASP difference minimization, while the OL approaches perform well for the minimization of the MSE and ASP regrets.

Spectrum sharing and full duplexing are two promising technologies for alleviating the severe spectrum crunch that has threatened to blight the progress of future wireless communication systems. In this paper, we consider a two tier coexistence framework involving a collocated multiple-input-multiple-output (MIMO) radar system (RS) and a full-duplex MIMO cellular system (CS). Considering imperfect channel state information and hardware impairments at the CS, we focus on a spectrum sharing environment to improve the quality of service (QoS) for cellular users by designing i) precoders at CS via the minimization of sum mean-squared-errors, subject to the constraints of transmit powers of the CS and probability of detection (PoD) of the RS, and ii) precoders at the RS to mitigate the interference from RS towards CS. While the monotonically increasing relationship between PoD and its non-centrality parameter is exploited to resolve the PoD in terms of interference threshold towards the RS, a generalized likelihood ratio test for target detection is used to derive detector statistics of the precoded radar waveforms. Numerical results demonstrate the feasibility of the proposed spectrum sharing algorithms, albeit with certain tradeoffs in RS transmit power, PoD and QoS of cellular users.

The co-channel interference (CCI) is one of the major impairments in wireless communication. CCI typically reduces the reliability of wireless communication links, but the "difficult" CCI which is no more or less stronger to the desired signals destroys wireless links despite having myriad of CCI mitigation methods. It is shown in this paper that M-QAM (Quadrature Amplitude Modulation) or similar modulation schemes which modulate information both in in-phase and quadrature-phase are particularly vulnerable to difficult CCI. Despite well-known shortcomings, it is shown in this paper that M-PAM or similar schemes that use a single dimension for modulation provides an important mean for difficult CCI mitigation.

In this paper, we consider interference channel model in which transmissions from multiple users are partially correlated. This correlation arises in wireless sensor network (WSN) scenarios and temporally correlated models. Considering this model, two minimum mean squared error (MSE) based precoding methods are derived. With these formulations, an iterative convergent procedure is formulated similar to a typical interference alignment (IA) algorithm. Simulations show that the second method provides the best sum rates for different correlation values.

To meet increasing demands of wireless multimedia communications, caching of important contents in advance is one of the key solutions. Optimal caching depends on content popularity in future which is unknown in advance. In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy in homogeneous Poisson point process (PPP) distributed caching network. Given a set of available placement strategies, simulations show that the presented framework successfully learns and provides the best content placement to maximize the average success probability.

In this paper we investigate the co-existence between a multi-cell multi-user (MU) full-duplex (FD) multiple-input multiple-output (MIMO) cellular network and a MIMO radar. While a joint beam-forming design technique at the cellular base-stations and users is proposed to maximize the detection probability of the MIMO radar subject to constraints of data rate per user in each cell and transmit power, null-space based waveform projection is used to mitigate the interference from the radar towards the cellular network. In particular, the proposed technique optimizes the performance of detection probability by maximizing its lower bound, which is obtained by exploiting the monotonically increasing relationship of detection probability and its non-centrality parameter. Numerical results show the feasibility of spectrum sharing between both systems.

Doppler effect is a fundamental phenomenon that appears in wave propagation, where a moving observer experiences dilation or contraction of the wavelength of a wave. It also appears in radio frequency (RF) wireless communication when there exists a relative movement between the transmitter and the receiver, and is widely considered as a major impairment for reliable wireless communication. The current paper proposes Doppler assisted wireless communication (DAWC) that exploits Doppler effect and uses kinetic energy for co-channel interference (CCI) mitigation. The proposed system also exploits the propagation environment and the network topology and consists of an access point (AP) with a rotating drum antenna. The rotating drum receive antenna is designed in such a way that it shifts the interfering signals away from the desired signal band. This paper includes a detailed system model, and the results show that under favorable fading conditions, CCI can be significantly reduced. Therefore, it is anticipated that more sophisticated wireless systems and networks can be designed by extending the basic ideas proposed herein.

In this paper, we investigate the feasibility of wireless edge caching in a hybrid millimeter-wave (mmWave)- micro-wave (μWave) network. Considering the average success probability (ASP) of file delivery as the performance metric, we derive expressions for the association probability of the typical user to the mmWave and μWave networks using stochastic geometric tools. Accordingly, we provide an upper bound on the ASP of file delivery and formulate the content caching placement scheme as an optimization problem with respect to caching probabilities, which jointly optimizes the ASP of file delivery considering both content placement and delivery phases. To simplify the non-convex problem and obtain design insights, we split it into two scenarios: 1) noise-limited and 2) interference-limited, and then propose optimal caching placement algorithms for both. We numerically evaluate the performance of the proposed schemes under several essential factors, such as content popularity, cache size, target data rate, blockages in the mmWave network, BS density, and path loss and also compare it with other common proactive caching schemes, namely uniform caching, caching M most popular files, and random caching. Numerical results demonstrate the superiority of the proposed caching scheme over others, albeit certain trade-offs.

In this paper, we investigate a full duplex (FD) multi-user non-orthogonal multiple access (NoMA) communication system based on the optimization of received signal-to-interference-plus-noise ratio (SINR) per unit power. Since the communication system operates in the FD mode, co-channel interference (CCI) and self-interference (SI) dominate the system's performance. Accordingly, to combat the CCI, we adopt a game-theoretic approach and propose users' clustering algorithms and to suppress the SI, we formulate an optimization problem to maximize the power-normalized SINR (PN-SINR). While the user clustering optimization problem is constrained by: 1) the successive interference cancellation (SIC) constraint and 2) two binary constraints for the allocations of uplink (UL) and downlink (DL) users, the PN-SINR problem is constrained by: 1) total transmit power budget at the base station and UL users; 2) the fundamental condition for the implementation of successive interference cancellation in the NoMA; and 3) the minimum fairness condition for the UL users. The original PN-SINR problem is non-convex and hence is converted into an equivalent subtractive-form problem, after which we propose an iterative algorithm to find the optimal power allocation policy. Properties of all the proposed algorithms are thoroughly investigated and the numerical results are provided. Based on the channel conditions and suppression level of SI and CCI, the superiority of the proposed FD-NoMA system over half-duplex NoMA and FD orthogonal multiple access systems is verified.

Doppler effect is a fundamental phenomenon that appears in wave propagation, where a moving observer experiences dilation or contraction of wavelength of a wave. It also appears in radio frequency (RF) wireless communication when there exists a relative movement between the transmitter and the receiver, and is widely considered as a major impairment for reliable wireless communication. The current paper proposes a wireless receiver that carefully exploits Doppler effect for cochannel interference mitigation. The proposed system-termed as DAIM to stand for Doppler Assisted Interference Mitigation-exploits the propagation environment and the network topology, and consists of an access point with a rotating drum antenna. The rotating drum receive antenna is designed in such a way that it shifts the interference signals away from the desired signal band. This paper includes a detailed system model and a simulation study. The results show that under favorable fading conditions, co-channel interference can be significantly reduced if not eliminated. Therefore, it is anticipated that more sophisticated wireless systems and networks can be designed by extending the basic system proposed herein.

In this paper, spectrum sharing between a multiple-input-multiple-output (MIMO) radar and a full duplex (FD) multi-user MIMO (MU-MIMO) cellular system is studied. While a joint transceiver design technique at a hardware impaired FD cellular system considering imperfect channel state information is developed to maximize the detection probability of the MIMO radar, null-space based waveform projection is proposed to mitigate the interference from the radar towards the cellular system. The proposed technique exploits the monotonically increasing relationship of detection probability and its non-centrality parameter and accordingly optimizes the performance of detection probability of the radar, while also providing the cellular users with specific quality-of-service (QoS). Numerical results demonstrate the feasibleness of spectrum sharing between both systems, albeit certain trade-offs in radar transmit power, detection probability and QoS of users in the cellular system.

We propose a novel transceiver design technique to facilitate flexible spectrum sharing between a multiple-input multiple-output (MIMO) radar and a full-duplex (FD) MIMO cellular system. The optimization problem for maximizing the rate of the cellular system is formulated, subject to the constraints of individual power at the uplink users, total power at the base station, and interference power towards the MIMO radar from the cellular system so that the detection probability of the radar is not hindered. We show that the above problem can be cast as a second-order cone programming problem and the joint design of transceiver matrices can be obtained through an iterative algorithm. Numerical results show that using the spectrum shared by the radar, the FD cellular system can achieve sum rate of up to 25-30 bits/sec/Hz for a reasonable self-interference cancellation of around -70 dB. However, to facilitate this, while also maintaining a detection probability of around 0.9, the radar needs to spend an extra power of around 2-3 dB.

A notable commonality in the existing studies on millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems is the assumption of perfect hardware during communication. However, this is a strong hypothesis since residual tranceiver hardware impairments (RTHIs) are inevitable in reality. Hence, this paper proposes a mmWave MIMO system that generalizes the state of the art by considering the inevitable RTHIs. We shed light on the impact of three major hardware impairments, namely, the multiplicative phase noise (PN), the amplified thermal noise (ATN), and the residual additive transceiver hardware impairments (RATHIs). In particular, we derive the spectral efficiency of the system under the presence of RTHIs. Additionally, we provide a detailed analysis to quantify the degradation caused to the spectral efficiency of the system by each separate impairment. Among the noteworthy outcomes is that the multiplicative PN is the most critical of the three impairments. Furthermore, we verify that the merits of the mmWave MIMO system are improved in line with large MIMO, which needs to be deployed in a cost-efficient manner.

Despite the importance of Rayleigh-product multiple-input multiple-output channels and their experimental validations, there is no work investigating their performance in the presence of residual additive transceiver hardware impairments, which arise in practical scenarios. Hence, this paper focuses on the impact of these residual imperfections on the ergodic channel capacity for optimal receivers, and on the ergodic sum rates for linear minimum mean-squared-error (MMSE) receivers. Moreover, the low- and high-signal-to-noise ratio cornerstones are characterized for both types of receivers. Simple closed-form expressions are obtained that allow the extraction of interesting conclusions. For example, the minimum transmit energy per information bit for optimal and MMSE receivers is not subject to any additive impairments. In addition to the exact analysis, we also study the Rayleigh-product channels in the large system regime, and we elaborate on the behavior of the ergodic channel capacity with optimal receivers by varying the severity of the transceiver additive impairments.

In this paper, we investigate the energy harvesting (EH) technique and accordingly design transceivers for a K link multiple-input multiple-output interference channel. Each link consists of two full-duplex (FD) Internet of Things (IoT) nodes exchanging information simultaneously in a bi-directional communication channel. All the nodes suffer from interference, in particular strong self-interference and inter-node interference, due to operating in FD mode and simultaneous transmission at each link, respectively. Further, we divide the received signal at each node into two parts. While one part of the signal is used for information decoding, the other part is used for EH. We jointly design the transmit and receive beamforming vectors and receiver power splitting ratios by minimizing the total transmission power of the system, subject to both signal-to-interference-plus-noise ratio and EH threshold constraints. Furthermore, the case of multiple-input single-output interference channel is also included for the sake of comparison. We also revisit the above problems for the case when the available channel state information (CSI) at the transmitters is imperfect, where the errors of the CSI are assumed to be norm bounded. Simulation results show that the EH technique can harvest enough energy to support power consumption limited IoT devices by aiding in recharging their respective batteries.

In this paper, the feasibility of spectrum sharing between a multiple-input multiple-output (MIMO) radar system (RS) and a MIMO cellular system (CS), comprising of a full-duplex (FD) base station (BS) serving multiple downlink and uplink users at the same time and frequency is investigated. While a joint transceiver design technique at the CS's BS and users is proposed to maximize the probability of detection (PoD) of the MIMO RS, subject to constraints of quality of service (QoS) of users and transmit power at the CS, null-space based waveform projection is used to mitigate the interference from RS toward CS. In particular, the proposed technique optimizes the performance of PoD of RS by maximising its lower bound, which is obtained by exploiting the monotonically increasing relationship of PoD and its non-centrality parameter. The numerical results show the utility of the proposed spectrum sharing framework, but with certain tradeoffs in performance corresponding to RS's transmit power, RS's PoD, CS's residual self-interference power at the FDBS and QoS of users.

Relay systems improve both coverage and system capacity. Toward this direction, a full-duplex (FD) technology, being able to boost the spectral efficiency by transmitting and receiving simultaneously on the same frequency and time resources, is envisaged to play a key role in future networks. However, its benefits come at the expense of self-interference (SI) from their own transmit signal. At the same time, massive multiple-input massive multiple-output systems, bringing unconventionally many antennas, emerge as a promising technology with huge degrees-of-freedom. To this end, this paper considers a multi-pair decode-and-forward FD relay channel, where the relay station is deployed with a large number of antennas. Moreover, the rate-splitting (RS) transmission has recently been shown to provide significant performance benefits in various multi-user scenarios with imperfect channel state information at the transmitter (CSIT). Engaging the RS approach, we employ the deterministic equivalent analysis to derive the corresponding sum-rates in the presence of interferences. Initially, numerical results demonstrate the robustness of RS in half-duplex (HD) systems, since the achievable sum-rate increases without bound, i.e., it does not saturate at high signal-to-noise ratio. Next, we tackle the detrimental effect of SI in FD. In particular, and most importantly, not only FD outperforms HD, but also RS enables increasing the range of SI over which FD outperforms HD. Furthermore, increasing the number of relay station antennas, RS appears to be more efficacious due to imperfect CSIT, since SI decreases. Interestingly, increasing the number of users, the efficiency of RS worsens and its implementation becomes less favorable under these conditions. Finally, we verify that the proposed DEs, being accurate for a large number of relay station antennas, are tight approximations even for realistic system dimensions.

A significant burden on wireless networks is brought by the uploading of user-generated contents to the Internet by means of applications such as social media. To cope with this mobile data tsunami, we develop a novel multiple-input multiple-output (MIMO) network architecture with randomly located base stations (BSs) a large number of antennas employing cache-enabled uplink transmission. In particular, we formulate a scenario, where the users upload their content to their strongest BSs, which are Poisson point process distributed. In addition, the BSs, exploiting the benefits of massive MIMO, upload their contents to the core network by means of a finite-rate backhaul. After proposing the caching policies, where we propose the modified von Mises distribution as the popularity distribution function, we derive the outage probability and the average delivery rate by taking advantage of tools from the deterministic equivalent and stochastic geometry analyses. Numerical results investigate the realistic performance gains of the proposed heterogeneous cache-enabled uplink on the network in terms of cardinal operating parameters. For example, insights regarding the BSs storage size are exposed. Moreover, the impacts of the key parameters such as the file popularity distribution and the target bitrate are investigated. Specifically, the outage probability decreases if the storage size is increased, while the average delivery rate increases. In addition, the concentration parameter, defining the number of files stored at the intermediate nodes (popularity), affects the proposed metrics directly. Furthermore, a higher target rate results in higher outage because fewer users obey this constraint. Also, we demonstrate that a denser network decreases the outage and increases the delivery rate. Hence, the introduction of caching at the uplink of the system design ameliorates the network performance.

The rapid growth of energy consumption due to the strong demands of wireless multimedia services, has become a major concern from the environmental perspective. In this paper, we investigate a novel energy-efficient resource allocation scheme for relay-assisted multiuser networks to maximize the energy efficiency (EE) of the network by jointly optimizing the subcarrier pairing permutation formed in one-to-many/many-to-one manner, subcarrier allocation, as well as the power allocation altogether. By analyzing the properties of the complex mixed-integer nonlinear programming problem, which is generally very difficult to solve in its original form, we transform the problem into an equivalent convex problem by relaxing the integer variables using the concept of subcarrier time sharing, and by applying a successive convex approximation approach. Based on the dual decomposition method, we derive an optimal solution to the joint optimization problem. The impact of different network parameters, namely number of subcarriers and number of users, on the attainable EE and spectral efficiency (SE) performance of the proposed design framework is also investigated. The numerical results are provided to validate the theoretical findings and to demonstrate the effectiveness of the proposed algorithm for achieving higher EE and SE than the existing schemes.

In this paper, we study an amplify-and-forward relay network with energy harvesting (EH) source and relay nodes. Both nodes can continuously harvest energy from the environment and store it in batteries with finite capacity. Additionally, the source node is capable of transferring a portion of its energy to the relay node through a dedicated channel. The network performance depends on not only the energy arrival profiles at EH nodes but also the energy cooperation between them. We jointly design power control and transfer for maximizing the sum rate over finite time duration, subject to energy causality and battery storage constraints. By introducing auxiliary variables to confine the accumulated power expenditure, this non-convex problem is solved via a successive convex approximation approach, and the local optimum solutions are obtained through dual decomposition. Also, when channels are quasi-static and the power control values of the source (relay) node are preset to a constant, a monotonically increasing power control structure with the time is revealed for the relay (source) node with infinite battery capacity. Computer simulations are used to validate the theoretical findings and to quantify the impact of various factors, such as EH intensity at nodes and relay position on the sum rate performance.

In this paper, we analyze the performance of a millimetre wave (mmWave) network where the base stations (BSs) equipped with very large uniform circular arrays (UCA) serve spatially distributed users. Due to its capability of scanning through both the azimuth as well as elevation dimensions, a 3D UCA is considered at the BSs to characterize the signal-to-interference-plus-noise ratio (SINR) of the network. Furthermore, stochastic geometric tools are employed while modelling the interference associated with a particular user. Thereby, expressions for coverage probability of the network is derived and validated in the numerical section. In particular, with the help of simulation results, we show the effect of the number of BS antennas, radius of the circular coverage area and different network parameters such as BS density, blockage density, path loss exponent, and SINR threshold on the coverage probability of the mmWave network.

In this paper, we propose a novel approach for the spectrum sharing between Multi-Input-Multi-Output (MIMO) radar and downlink multi-user Multi-Input- Single-Output (MU-MISO) communication system. To obtain a power-efficient beamforming at the base station (BS), we utilize the constructive multi- user interference (MUI) as a source of green signal power. The proposed beamforming design mainly focuses on two optimization problems, i.e., transmit power minimization for BS and interference minimization for radar, subject to given performance requirements of the two systems. We further consider the impact of the proposed methods on radar, where the detection probability for MIMO radar in the presence of the interference from BS is analytically derived, and important trade-offs are revealed. Numerical results show that the proposed approach outperforms the conventional beamforming designs by achieving a significant performance gain under the discussed coexistence scenario.

Full-duplex (FD) systems, suggested to play a key role in future networks, boost the spectral efficiency, although they suffer from self-interference (SI). In parallel, massive multiple-output (MIMO) systems, employing a large number of antennas, emerge as a promising technology offering huge degrees-of-freedom. Hence, after careful consideration, this paper considers a multi-pair decode-and-forward FD relay channel, where the relay station is deployed with a large number of antennas. Also, since the rate-splitting (RS) transmission is applicable in multi-user scenarios, we include it in our analysis in terms of deterministic equivalents. Remarkably, numerical results show the robustness of RS both half-duplex (HD) and FD systems. Moreover, RS increases the range of SI over which FD outperforms HD. Outstandingly, RS proves to be more robust as the number of relay antennas increases.

The rapid growth in energy consumption due to strong demands of wireless multimedia services, has become a major concern from an environmental perspective. In this paper, we investigate a novel energy-efficient resource allocation scheme for relay-assisted multiuser networks to maximize the energy efficiency (EE) of the network by jointly optimizing the subcarrier pairing permutation formed in one-to-many/many-to-one manner, subcarrier allocation, as well as the power allocation all together. By analyzing the properties of the complex mixed-integer nonlinear programming problem, which is generally very difficult to solve in its original form, we transform the problem into an equivalent convex problem by relaxing the integer variables using the concept of subcarrier time sharing, and by applying a successive convex approximation approach. Based on the dual decomposition method, we derive an optimal solution to the joint optimization problem. Numerical results are provided to validate the theoretical findings and to demonstrate the effectiveness of the proposed algorithms.

In this work we focus on a cellular network where a full-duplex (FD) base-station (BS) communicates with multiple half-duplex (HD) downlink (DL) and uplink (UL) users. The introduction of FD capability at the BS causes a surge in the amount of interference compared to the HD network counterpart. In particular a new type of co-channel interference arises between UL and DL data, since they are transmitted simultaneously. Here, we consider the use of linear interference alignment (IA) to manage interference in such networks, under the availability of imperfect channel state information (CSI). We design two novel IA algorithms, the first is based on maximizing the signal-to-interference-plus-noise ratio (Max-SINR) and the second minimizes the mean squared error (MMSE). Both algorithms, 1) take into effect statistical knowledge of the CSI error for added robustness, 2) follow specific design principles that distribute the different interference components amongst the various beamformers, and 3) result in unitary precoders and receivers. Additionally, we show that under certain conditions the proposed Max-SINR and MMSE designs obtain identical beamformers.

We consider the beamforming design to maximize the energy-efficiency (EE) of a K link multiple-input multiple-output (MIMO) interference channel, where each link consists of two full-duplex (FD) nodes. We first transform the original fractional form optimization problem into an equivalent subtractive-form optimization problem by exploiting the properties of fractional programming, and then perform a two-layer optimization scheme. In the outer layer, the EE parameter is searched using a simple one-dimensional search, and in the inner layer, the relationship between Weighted-Sum-Rate (WSR) and Weighted Minimum-Mean-Squared-Error (WMMSE) problems is exploited to solve the subtractive form optimization problem. Simulation results show that the EE of FD systems is lower than that of half-duplex (HD) systems, as FD nodes need to overcome self-interference (SI) which leads to high power consumption.

This work encompasses Rate-Splitting (RS), providing significant benefits in multi-user settings in the context of huge degrees of freedom promised by massive Multiple-Input Multiple-Output (MIMO). However, the requirement of massive MIMO for cost-efficient implementation makes them more prone to hardware imperfections such as phase noise (PN). As a result, we focus on a realistic broadcast channel with a large number of antennas and hampered by the unavoidable PN. Moreover, we employ the RS transmission strategy, and we show its robustness against PN, since the sum-rate does not saturate at high signal-to-noise ratio (SNR). Although, the analytical results are obtained by means of the deterministic equivalent analysis, they coincide with simulation results even for finite system dimensions.

In this paper, we investigate resource allocation algorithm for multiuser full-duplex (FD) decode-and-forward (DF) relay network for improving the energy efficiency (EE). The problem of energy-efficient joint subcarrier and power allocation is formulated as a ratio of the spectral efficiency (SE) of the network to the total energy consumption in the network. The formulated problem is a non-convex fractional mixed binary-integer non-linear programming problem. Further, we resolve this problem by a series of convex transformations and introduce a network penalty factor, which works as EE parameter, to convert the fractional mixed-integer form into a parametric subtractive form, and then design an effective energy-efficient iterative resource allocation algorithm to find the optimal solution. In addition, we also propose a low-complexity suboptimal algorithm. The effectiveness of the proposed iterative and suboptimal algorithms are evinced by simulation results.

In this paper, we investigate an energy-efficient joint subcarrier and power allocation algorithm for improving the worst energy efficiency (worst-EE) in multiuser two-way amplify-and-forward (AF) relay networks, that not only balances the EE of the two-way links, but also ensures the desired quality-of-service (QoS) of each user. In order to maximize the worst-EE, an EE-balancing optimization problem is formulated as the ratio of the spectral efficiency (SE) over the total network power consumption subject to a total transmit power and users' QoS constraints. Since the formulated primal problem is a non-convex fractional mixed binary-integer program, i.e., NP-hard to solve, thus a concave lower bound on the objective function and a series of convex transformations are applied to transform the problem into a tractable convex form. An iterative algorithm is proposed to achieve the optimal solution of the dual problem. We further propose an efficient, low-complexity suboptimal resource allocation algorithm. Simulation results demonstrate the effectiveness of the proposed iterative and suboptimal algorithms.

The explosion of cellular users and high demand for data has evolved the single-tier cellular network to multi-tier network. This paper analyses the gain of non-orthogonal multiple access (NOMA), an enabling technique for 5G, in a heterogeneous cellular network (HCN) consisting of a macro base station (MBS) tier and femto base station (FBS) tier. Offloading users to the FBS tier is performed to relieve the MBS tier of over congestion. In order to support offloaded user, the FBS tier employs NOMA. The results are plotted for different channel conditions while offloading the user to FBS tier. Benefits of NOMA (for e.g., higher ergodic rate, user fairness, performance enhancement at cell edge user) are observed for different channel conditions for the offloaded user. It is also observed that offloading to FBS tier with NOMA gives better performance as compared to offloading without NOMA.

The authors consider secret communication through a relay‐assisted cognitive interference channel in which primary and secondary base stations (SBSs), respectively, communicate with the primary and secondary receivers (PU‐Rx and SU‐Rx) in the presence of multiple eavesdroppers. An SBS is allowed to transmit simultaneously with the primary base station (PBS). They propose three cooperative jamming (CJ) schemes based on the available channel state information at the base stations and the relay. The proposed CJ schemes are designed to create additional interference in the direction of eavesdroppers without creating any interference to the PU‐Rx and the SU‐Rx. A combined approach of beamforming and zero‐forcing precoding is developed at the PBS, the SBS and the relay to cancel out jamming interference at the PU‐Rx and the SU‐Rx. The secrecy rate of SU‐Rx is calculated with the constraint of maintaining interference temperature at the PU‐Rx under a certain threshold. Compared with the direct transmission schemes that are available in the literature, the authors’ results show that the approach which combined beamforming and CJ significantly improves the secrecy rate of the cognitive interference channel.

In this work, the performance of a dual‐hop amplify‐and‐forward (AF) multi‐antenna relaying system over Rayleigh fading channels with random co‐channel interference (CCI) is investigated. Three receiving strategies such as the maximal‐ratio combining (MRC), zero‐forcing (ZF) and minimum mean square error (MMSE) are employed in the relay to mitigate the impact of CCI which follows a Poisson point process. In second hop, the relay forwards the signal to the destination by using maximum ratio transmission (MRT). Specifically, we derive the asymptotic expressions of the capacities for this system. The simulation and analytical results show that the MMSE/MRT scheme always provides significant improvement on capacity compared with MRC/MRT and ZF/MRT schemes. Furthermore, the MRC/MRT scheme gives almost the same performance as the MMSE/MRT scheme when the density of CCI sources is high.

In this paper, we focus on a multi-user multi-cell scenario with full-duplex (FD) base-stations and half-duplex (HD) downlink (DL) and uplink (UL) users, where all nodes are equipped with multiple antennas. Our goal is to design filters for weighted sum rate (WSR) maximization whilst taking into consideration the effect of transmitter and receiver distortion. Since WSR problems are non-convex, we exploit the relationship between rate and mean squared error in order to propose low complexity alternating optimization algorithms, which are guaranteed to converge. While the initial design assumes perfect channel state information (CSI), we also move beyond this assumption and consider WSR problems under imperfect CSI. This is done using two types of error models; the first is a norm-bounded error model, suitable for cases where the CSI error is dominated by quantization issues, and the second is a stochastic error model, suitable for errors that occur during the channel estimation process itself. Results show that rates achieved in FD mode are higher than those achieved by the baseline HD schemes and demonstrate the robust performance of the proposed imperfect CSI designs. In addition, we also extend our original WSR problem to one which maximizes the total DL rate subject to each UL user achieving a desired target rate. This latter design can be used to overcome potential unfairness issues and ensure that all UL users are equally served in every time slot.

In this paper, we consider a system where full-duplex (FD) base-stations (BSs) communicate with half-duplex (HD) downlink (DL) and uplink (UL) users in a multi-user multi-cell network, where all nodes are equipped with multiple antennas. The introduction of FD BSs offers potential to increase spectral efficiency, however, it also causes a surge in the number of interference links compared with the HD network counterpart. Here, we apply linear interference alignment (IA) to manage interference in this network under imperfect channel state information (CSI). First, we characterize the performance losses incurred with respect to the achievable sum rate and degrees of freedom (DoFs). Results show that the general trend in performance loss is mainly determined by how the error scales with the signal-to-noise ratio (SNR). In particular, full UL and DL DoF can be achieved even under imperfect CSI when the channel error is at least inversely proportional to SNR. Moreover, in such cases the sum rate loss is always finite, and either goes to zero or is upper bounded by a derived value. Second, we design two linear IA algorithms applicable to the system under consideration. These are based on minimizing the mean square error (MMSE) and maximizing the signal-to-interference-plus-noise ratio, and consider statistical knowledge of the CSI error for added robustness. The proposed algorithms follow specific design principles that distribute the different interference components amongst the various beamformers and result in unitary receivers and precoders. In addition, we show that under certain conditions both designs result in identical beamforming solutions, even though the MMSE algorithm has lower computational complexity. Finally, we also derive the proper condition for IA feasibility in the multi-cell system under consideration.

In this paper, we investigate utility-based joint subcarrier and power allocation algorithms for improving the energy efficiency (EE) in multi-user two-way regenerative relay networks. With the objective of determining the best subcarrier allocation for each user pair, subcarrier pairing permutation, and power allocation to all the nodes, a network price is introduced to the power consumption as a penalty for the achievable sum rate, followed by the examination of its impact on the tradeoff between the EE and spectral efficiency. The formulated optimization problem is a non-convex mixed-integer nonlinear programming problem, and thus a concave lower bound on the objective function and a series of convex transformations are applied to transform the problem into a convex one. Through dual decomposition, we propose a utility-based resource allocation algorithm for iteratively tightening the lower bound and finding the optimal solution of the primal problem. By exploring the structure of the obtained optimal solution, an optimal price that enables green resource allocation is found from the perspective of maximizing EE. Additionally, a suboptimal algorithm is investigated to strike a balance between computational complexity and optimality. Simulation results evince the effectiveness of the proposed algorithms.

In this paper, we analyze the secrecy characteristics of random wireless networks using stochastic geometric tools. The locations of the source and eavesdropper nodes are modeled as independent 2-D Poisson point processes. We investigate the secrecy outage probability of such networks from the perspective of the k th best source, which has still not been well characterized. In particular, we derive the received path gain distributions of the typical destination and the eavesdropper from the k th best source. Furthermore, we introduce a novel concept of security-region based on the k th best source index. This is pragmatic in creating a protected communication zone for the typical destination and also to bind the number of sources that can coordinate in a coordinated multi-point transmission (CoMP) network. We further derive the secrecy outage probability for these CoMP sources based on the security-region. We also provide a closed-form expression for the maximum number of eavesdroppers for a given secrecy outage constraint, which can effect the secure communication. Tractable numerical, and simulation results are presented under various assumptions of densities, path loss exponents, and antenna figures.

Electronically steerable parasitic array radiator (ESPAR) technology enables the implementation of antenna arrays of a number of elements with a single radio frequency (RF) source. Two approaches to achieve stable transmission using an ESPAR antenna (EA) are to increase the self-resistance of an EA or to transmit signals closely approximating the actual signals that keep the EA stable. Both approaches did not take into account the impact of limited power on an EA transmission, which is a practical constraint on power amplifier design. We propose a new transmission scheme to enable an EA to provide stable multiple antenna functionality taking into account the instantaneous total power requirement. This problem is formulated as a non-convex optimization problem and it is solved analytically by coordinate transformation and geometric analysis. The optimal approximate signals are obtained using root finding and interior-point algorithms. Moreover, it is shown through simulations that our proposed scheme achieves similar symbol error rate performance to that of the standard multiple antenna transmitter with multiple RF chains under power limited single-user and multi-user transmission scenarios. Furthermore, it is shown that increasing the self-resistance of an EA to achieve stability is highly power inefficient.

In this paper, a novel resource allocation algorithm is investigated to maximize the energy efficiency (EE) in multiuser decode-and-forward (DF) relay interference networks. The EE optimization problem is formulated as the ratio of the spectrum efficiency (SE) over the entire power consumption of the network subject to total transmit power, subcarrier pairing, and allocation constraints. The formulated problem is a nonconvex fractional mixed binary integer programming problem, i.e., NP-hard to solve. Furthermore, we resolve the convexity of the problem by a series of convex transformations and propose an iterative EE maximization algorithm to jointly determine the optimal subcarrier pairing at the relay, subcarrier allocation to each user pair and power allocation to all source and the relay nodes. Additionally, we derive an asymptotically optimal solution by using the dual decomposition method. To gain more insights into the obtained solutions, we further analyze the resource allocation algorithm in a two-user case with interference-dominated and noise-dominated regimes. In addition, a suboptimal algorithm is investigated with reduced complexity at the cost of acceptable performance degradation. Simulation results are used to evaluate the performance of the proposed algorithms and demonstrate the impacts of various network parameters on the attainable EE and SE.

In this paper, we study the problem of energy-efficient resource allocation in multiuser two-way amplify-and-forward (AF) relay networks with the aim of maximizing the energy efficiency (EE), while ensuring the quality-of-service (QoS) requirements and balancing the EE of the user links. We formulate an EE-balancing optimization problem that maximizes the ratio of the spectral efficiency (SE) over the total power dissipation subject to QoS and a limited transmit power constraints. The problem which maximizes the EE by jointly optimizing the subcarrier pairing, power allocation, and subcarrier allocation, turns out to be a non-convex fractional mixed-integer nonlinear programming problem, which has an intractable complexity in general. We apply a concave lower bound on the achievable sum rate and a series of convex transformations to make the problem convex one and propose an iterative algorithm for iteratively tightening the lower bound and finding the optimal solution through dual decomposition approach. In addition, a low-complexity suboptimal algorithm is investigated. We then characterize the impact of various network parameters on the attainable EE and SE of the network employing both EE maximization and SE maximization algorithms when the network is designed from the EE perspective. Simulation results demonstrate the effectiveness of the proposed algorithms.

In this paper, we analyse the performance of a millimeter wave (mmWave) cloud radio access network (CRAN), where remote radio heads (RRHs) are modelled as a homogeneous Poisson point process (PPP) and blockages are randomly distributed. In contrast to the previous works on CRAN that operate below 6GHz, we consider CRAN operating in mmWave range (30-300 GHz). Since blockages have a significant impact on mmWave communications, we adopt a distance-dependent line-of-sight (LOS) probability function and model the locations of the LOS and non-line-of-sight (NLOS) RRHs as two independent non-homogeneous PPP. The outage performance and ergodic capacity of the LOS and NLOS RRHs are analysed and compared. When the RRH with the best channel is selected for transmission, the expressions of outage probability and throughput are provided. The presented results show that due to the severe path loss in NLOS links, in low transmitted power regime, the best RRH (BR) is always LOS. However, in high transmitted power regime, NLOS RRHs can be BR.

In this paper, energy-efficient resource allocation algorithms are investigated to improve the energy efficiency (EE) in two-way multi- carrier amplify-and-forward (AF) relay networks by ensuring the quality-of-service (QoS) and balancing the EE of the user links. We formulate an EE-balancing optimization problem that maximizes the ratio of the spectral efficiency (SE) and the total network power consumption by jointly designing the subcarrier pairing at the relay node and power allocation at all nodes under the total transmit power and QoS constraints, thereby leading to a mixed integer programming problem which turns out to be non-convex. Further, we resolve the problem by a series of convex transformations and propose an iterative EE algorithm to determine the solution through Lagrangian dual decomposition. Moreover, a suboptimal EE algorithm is also investigated with reduced complexity at the cost of acceptable performance degradation. Simulation results validate the performance gain of the proposed algorithms and show the performance tradeoff between EE and SE.

In this paper, the performance of a cloud radio access network (CRAN) is analysed, which consists of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS). Different from previous works on CRAN where Poisson Point Process (PPP) is used to model spatial distribution of RRHs, a more realistic Matern Hard-core point process (MHCPP) model is adopted in this work. To compare system performance of CRAN when different transmission strategies are used, two RRH selection schemes are adopted including 1) the best RRH selection (BRS) and 2) all RRHs participation (ARP). Considering downlink transmission, the outage probability and system throughput of CRAN are analytically characterized. The presented results demonstrate that compared to PPP model, the presence of hard-core distance will increase outage probability. Furthermore, the BRS scheme is more energy-efficient than the ARP scheme. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance.

The secrecy outage of millimeter wave (mmWave) networks under the impact of blockages is derived. Specifically, using a network model that accounts for uncertainties both in node locations and blockages, we characterize the connection outage probability and the secrecy outage probability of mmWave networks with multiple eavesdroppers under basic factors such as density of eavesdropping nodes, antenna gain and blockage density. As a desirable side effect, certain factors such as blockages and reduced antenna gain can decrease the secrecy outage probability. This however is in contrast to general mmWave systems where it has been shown that reduced blockages and high antenna gains provide higher capacities.

We examine the deployment of a large multi-user multiple-input multiple-output (MIMO) system and the resulting Energy Efficiency (EE) considering a 2D rectangular array with increasing antenna elements within a fixed physical space. The resulting increasing mutual coupling and correlation among the base station (BS) antennas are incorporated by deriving a practical mutual coupling matrix which considers coupling among all antenna elements. We also provide a realistic analysis of the energy consumption using a new model, taking into account the circuit power consumption as a function of the number of BS antennas and then present a performance analysis of the system with respect to EE. Our analysis shows that while spectral efficiency increases with increasing number of BS antennas in a massive MIMO system, EE does not increase boundlessly when the increasing number of antennas are to be accommodated within a fixed physical space and the total power consumed is considered to be a function of the BS antennas. Accordingly, analytic expressions for the optimum number of antennas to attain maximum EE are obtained.

The potential benefits of deploying relays in outdoor millimeter-wave (mmWave) networks are investigated. We derive the coverage probability from sources to a typical destination for such systems aided by relays. The sources and the relays are modeled as independent homogeneous Poisson point processes. We present a relay modeling technique for mmWave networks considering blockages and compute the density of active relays that aid the transmission. Closed form expressions for end-to-end signal to noise ratio for two relay selection techniques, namely best path selection and best relay selection are derived. Finally, we analyze the coverage probability and transmission capacity of the network and validate them with simulation results. Our results show that the coverage probability and transmission capacity of mmWave systems, which are often affected by extensive blockages can be increased considerably with the aid of relays.

We study a full duplex (FD) multiple-input multiple-output (MIMO) cognitive cellular network, in which a secondary base-station (BS) operating in FD mode serves multiple uplink (UL) and downlink (DL) secondary users (SUs) operating in half-duplex (HD) mode simultaneously. The spectrum is shared between secondary and primary networks, and thus uplink SUs and secondary BS generate interference on primary users (PUs). We assume that the channel state information (CSI) available at the transmitters is imperfect, and the errors of the CSI are assumed to be norm bounded. Under the impact of channel uncertainty, we address the robust minimization of the sum of mean-squared-errors (MSE) of all estimated symbols subject to power constraints at the uplink SUs and secondary BS, and interference constraints projected to each PU. We show that this problem can be cast as a Semidefinite programming (SDP), and joint design of transceiver matrices can be obtained through an iterative algorithm. Numerical results are presented to show the effectiveness and robustness of the proposed robust algorithm.

The secrecy characteristics of random wireless networks considering a generalized fading model, where the communication nodes are equipped with multiple antennas is analyzed. Using stochastic geometric tools, we investigate the secrecy outage probability of such networks from the perspective of the kth best source, which has still not been well characterized in the literature. In particular, we derive the received path gain distributions of the typical destination and the eavesdropper from the k-th best source. Using these results, we derive the secrecy outage probability for two scenarios with respect to the received path gain from any best source and the k-th best source. Furthermore, we introduce a novel concept of security-region based on the k-th best source index. This is pragmatic in creating a protected communication zone for the typical destination. Tractable numerical and simulation results are presented under various assumptions of fading, path loss exponents and antenna figures.

Recently, the new concept of Licensed Shared Access/Authorized Shared Access (LSA/ASA) has emerged as a feasible commercial version of dynamic spectrum reuse based on Cognitive Radio (CR) technologies, e.g., via spectrum sensing or by exploiting geo-location information. This paper considers the problem of effective spectrum sharing between a colocated Multiple-Input-Multiple-Output (MIMO) radar that monitors the existence of a target and a wireless communications system. More specifically, the investigated scenario considers the downlink of a communications system represented by a Base Station (BS) trying to reuse the spectrum allocated for a colocated MIMO radar in order to communicate with an assigned terminal, in the vicinity of the radar system. We present an accurate model for the operation of the wireless system in the downlink, while the MIMO radar tries to maintain an acceptable detectability level of a target in the far field. The target detection problem is reformulated using a sensing approach based on energy detection, while the BS applies beamforming to null the interference created at the radar receiver. Based on the theory of Hermitian quadratic forms and with the aid of the Linearly Constrained Minimum Variance (LCMV) beamforming solution, the performance of target detection, when the MIMO radar coexists with the data transmission is quantified and numerical results show that spectral coexistence is feasible.

This paper studies the energy efficiency (EE) of the cloud radio access network (C-RAN), consisting of multiple remote radio heads (RRHs) equipped with electronically steerable parasitic array radiator (ESPAR) antennas, which provide multiple antenna functionality with a single radio frequency (RF) chain. An EE optimization problem is formulated to obtain the configuration of ESPAR and the closed-form expressions of the voltage feeding and the loadings are derived for signal transmission at each RRH. Specifically, we obtain the closed-form expressions for precoder and power allocation that are applicable not only for the ESPAR based system but also for standard MIMO antenna (SMA) system with multiple RF chains. It is shown that EA system can be configured with less complexity compared with SMA system in block fading channel. Furthermore, symbol error rate (SER) and EE performances are compared for EA and SMA based systems. It is shown that the system with EA provides better EE performance while providing similar SER performance. From our results, it is proved that EA system can provide better performance to satisfy the requirement of 5G wireless communication networks.

We consider a single cell multiple-input multiple-output (MIMO) system, where a base-station (BS) operating in full-duplex (FD) mode serves multiple uplink (UL) and downlink (DL) mobile users operating in half-duplex (HD) mode, simultaneously. The self-interference at the BS, and co-channel interference (CCI) from UL users to DL users are both taken into account. We consider the transmit and receive filter design for sum- rate maximization subject to a sum-power constraint at the BS and individual power constraints at each UL user of the system under the limited dynamic range considerations at the transmitters and receivers. By reformulating this non-convex problem as an equivalent component-wise convex optimization problem with the addition of two auxiliary variables, we propose a low complexity algorithm which converges to a stationary point.

Topological interference management is the study of achievable rates within communication networks with no channel state information at the transmitter (CSIT) beyond knowledge of the network structure itself. In this work, we study the degrees of freedom (DoF) of a two-cell two-user-per-cell interference broadcast channel (IBC) with alternating connectivity and global topological interference management. The topological information allows transmitters to track the changing network topology and exploit the varying connectivity states to achieve a DoF gain. We derive novel DoF outer bounds for the two-cell two-user-per-cell IBC with alternating connectivity. This analysis is carried out for different system configurations, namely, single-input single-output (SISO), multiple-input single-output (MISO), and multiple-input multiple-output (MIMO) systems. While global channel knowledge is always restricted to topological information only, we introduce a mixed CSIT setting where varying degrees of local CSIT availability are considered depending on the system configuration. Additionally, we investigate the achievability of the derived bounds and propose new transmission schemes based on joint coding across states. Results show that DoF higher than those conventionally obtained without global topological information are achievable, indicating that even such a minimal level of global CSIT is still highly useful.

We consider a K link multiple-input multiple-output interference channel where each link consists of two full-duplex (FD) nodes. Two transmit beamforming design problems are solved: 1) sum-power minimization problem subject to rate constraints and 2) energy-efficiency maximization problem subject to individual power constraints. To tackle the sum-power minimization problem, we first generalize the well-known relationship between weighted-sum-rate (WSR) and weighted minimum-mean-squared-error (WMMSE) problems, originally used to solve the sum-rate maximization problems, and then propose a low complexity centralized algorithm, which converges to a stationary point. To decrease the exchange of a huge amount of data and excessive signaling traffic among the nodes, a distributed algorithm is also proposed. For the energy-efficiency maximization problem, the original fractional form optimization problem is first transformed into an equivalent subtractive-form optimization problem by exploiting the properties of fractional programming, and then performs a dual-layer optimization scheme. In the outer layer, the energy-efficiency parameter is searched using a simple 1-D search, and in the inner layer, the relationship between WSR and WMMSE is exploited to solve the subtractive form optimization problem. Since the proposed algorithms require perfect channel-state-information, which is difficult to acquire in practice, we also propose a robust design, by taking the imperfect channel knowledge into consideration. It is shown in the simulations that the sum-power achieved in FD mode depends heavily on the transmitter/receiver distortion. Also the energy-efficiency of FD systems is lower than that of half-duplex systems, as FD nodes need to overcome self-interference and increased inter-user interference, which leads to high power consumption.

The secrecy outage of millimeter wave (mmWave) overlaid micro-wave (μWave) networks under the impact of blockages is analyzed, and closed form as well as integral expressions are provided. Specifically, using a network model that accounts for uncertainties both in node locations and blockages, we characterize the conditional connection outage probability and the secrecy outage probability of hybrid networks with multiple eavesdroppers under basic factors, such as density of eavesdropping nodes, antenna gain, and blockage density. The upper and lower bounds of the conditional secrecy outage probability for both the line-of-sight and non-line-of-sight links are derived. As a desirable side effect, certain factors, such as blockages and reduced antenna gain, can decrease the secrecy outage probability in mmWave networks. This can be considered as a tradeoff between outage capacity and secrecy outage capacity with respect to blockages. Hence, blockages that have been proved to be detrimental to achieving higher data rates in mmWave systems, can be helpful for systems with secrecy constraints. Finally, we have shown the coexistence of mmWave and μWave networks from a secrecy perspective.

Massive multiple-input-multiple-output (MIMO) systems deploying a large number of antennas at the base station (BS) have been shown to produce high spectral and energy efficiency (EE) under the assumptions of increasing BS physical space and critical antenna spacing. We examine the deployment of massive MIMO systems and resulting EE with a more realistic scenario considering a 2-D rectangular array with increasing antenna elements within a fixed physical space. Mutual coupling and correlation among the BS antennas are incorporated by deriving a practical mutual coupling matrix which considers coupling among all antenna elements within a BS. We also provide a realistic analysis of the energy consumption using a model, which takes into account the circuit power consumptions as a function of the number of BS antennas and then present a performance analysis of two practical low complexity detectors/receivers keeping EE into consideration. The simulation results obtained show that EE does not monotonically increase with the number of BS antennas. On the contrary, it is a decreasing concave or quasi-concave function of the number of BS antennas depending on the detection technique used at the receiver. We also show that with decreasing spacing between the antennas, mutual coupling increases, contributing toward reduction in EE. Our analysis thus shows that EE does not increase infinitely in a massive MIMO system when the increasing number of antennas are to be accommodated within a fixed physical space and the total power consumed is considered to be a function of the antennas. Accordingly, closed-form expressions for the optimum number of antennas to attain maximum EE for zero forcing (ZF) are obtained.

In this paper, the operation of a licensed shared access system is investigated, considering downlink communication. The system comprises a multiple-input-single-output (MISO) incumbent transmitter (TX)-receiver (RX) pair, which offers a spectrum sharing opportunity to a MISO licensee TX-RX pair. Our main contribution is the design of a coordinated transmission scheme, inspired by the underlay cognitive radio (CR) approach, with the aim of maximizing the average rate of the licensee, subject to an average rate constraint for the incumbent. In contrast to most prior works on the underlay CR, the coordination of the two TXs takes place under a realistic channel state information (CSI) scenario, where each TX has solely access to the instantaneous direct channel of its served terminal. Such a CSI knowledge setting brings about a formulation based on the theory of Team Decisions, whereby the TXs aim at optimizing a common objective given the same constraint set, on the basis of individual channel information. Consequently, a novel set of applicable precoding schemes consisting in letting the two TXs cooperate on the basis of the statistical information is proposed. We verify by simulations that this novel, practically relevant, coordinated precoding scheme outperforms the standard underlay CR approach.

In this paper, the problem of joint design of spectrum sensing (SS) and receive beamforming, with reference to a cognitive radio (CR) system, is considered. The aim of the proposed design is the maximization of the achievable average uplink rate of a secondary user, subject to an outage-based quality-of-service constraint for primary communication. A hybrid CR system approach is studied, according to which the system either operates as an interweave (i.e., opportunistic) or as an underlay (i.e., spectrum sharing) CR system, based on SS results. A realistic channel state information framework is assumed, according to which the direct channel links are known by the multiple antenna receivers, while merely statistical (covariance) information is available for the interference links. A new closed-form approximation is derived for the outage probability of primary communication, and the problem of rate-optimal selection of SS parameters and receive beamformers is addressed for hybrid, interweave, and underlay CR systems. It is proved that our proposed system design outperforms both underlay and interweave CR systems for a range of system scenarios.

In this paper, we analyze the performance of a cloud radio access network (CRAN), consisting of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS), each equipped with multiple antennas. To model the spatial distribution of RRHs and analyze its performance, we use stochastic geometry tools. In contrast to previous works on CRAN that consider Poisson Point Process (PPP) model for the spatial distribution of RRHs, we consider a more realistic Matérn hard-core point process (MHCPP) model that imposes a certain minimal distance (referred to as hard-core distance) between the two RRHs so that the RRHs are not too close to each other. To compare system performance of CRAN when different transmission strategies are used, three RRH selection schemes are adopted including 1) the best RRH selection (BRS); 2) all RRHs participation (ARP); and 3) nearest RRH selection (NRS). Considering downlink transmission, the ergodic capacity, outage probability, and system throughput of CRAN are analytically characterized for different RRH selection schemes. The presented results demonstrate that compared to PPP model, the increase in hard-core distance will result in a higher outage probability and cause a negative impact on ergodic capacity. Furthermore, when the same total transmit power is consumed, BRS scheme provides the best outage performance while ARP scheme is the best RRH selection scheme when the same transmit SNR at each RRH is assumed. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance. We extend our work to multiuser case with zero-forcing (ZF) precoding where it is proven that the results in multiuser case reduce to the derived results in this work by substituting K=1 for single-user.

This paper considers a frequency domain approach for the problem of spectrum sensing based on the multitaper detector combined with singular value decomposition. We present the exact closed forms for the performance of the MTM-SVD processor over fading channels. This is achieved through formulating the decision statistic as a Hermitian form, which is shown to be a hypoexponential variable where the distribution parameters are determined by the number of discrete prolate spheriodal sequences (DPSSs), number of cooperating users and frequency resolution. Also, we formulate the nonzero eigenvalues associated with the Hermitian form, which act as the distribution parameters for both cases of the null and the alternate hypotheses. We accurately formulate the probabilities of false alarm and missed detection, where we also accurately bound the average probability of missed detection over Rayleigh channels. As a general trend, the performance of the MTM-SVD method is enhanced when increasing the number of DPSSs or increasing the number of cooperating sensing nodes. Moreover, the obtained results show that the MTM-SVD processor outperforms the case of using the Periodogram even when large sensing frames are employed.

Topological interference management refers to the study of achievable rates within communication networks with no channel state information at the transmitter (CSIT) beyond knowledge of the network structure itself. In this work we consider the topological interference management problem within the context of a two cell two user interference broadcast channel (IBC) with alternating connectivity. Topological information, even though minimal, allows the transmitters to track the changing network structure and then exploit the varying connectivity states to obtain a degrees of freedom (DoF) gain. Thus, the main result of this work is the derivation of a novel outer bound on the DoF achievable by the two cell two user IBC in an alternating connectivity scenario. Additionally, we propose a scheme based on joint coding across states that achieves this outer bound for the case where all alternating connectivity states are equiprobable.

We perform an analysis of the secrecy outage of random networks under Nakagami-m fading with multiple transmit antennas. Specifically, using a network model that accounts for uncertainties both in node locations (distances) and channel coefficients (fading), we derive the distribution of the best path gain of eavesdroppers using Probability Generating Functional property of Poisson Point Process (PPP). Using this result, the secrecy outage probability and the conditional secrecy outage probability of random networks with multiple eavesdroppers are obtained, with basic factors such as the density of eavesdropping nodes, the number of transmit antennas and the fading coefficient all accounted for by explicit parameters. The impact of transmission factors, including number of transmit antennas, fading figure, legitimate node distance and node density are studied and analysed in numerical results.

Electronically steerable parasitic array radiator (ESPAR) antennas have been proposed to obtain multiple antenna functionality with only a single radio frequency (RF) chain. However, some signals cannot be transmitted using the ESPAR antennas (EA), because for those signals, the real part of the input impedance (RII) of the EA becomes negative. A negative input impedance implies that the EA cannot be realized and even if it is, it will not transmit that signal. In this work, we obtain approximate signals, which are close to the ideal signals in the mean square error (MSE) sense, for transmission that satisfy the requirement on input impedance. Specifically, we formulate and solve an optimization problem to minimize the MSE between the ideal and the approximate signals taking into account the constraint on the input impedance. We obtain closed-form expression for the approximate currents vector, thus, simplifying the processing at the transmitter. Our simulation results show that the EA system, transmitting the approximate signal, performs nearly the same as the standard multiple RFs antenna (SMA) system.

Topological interference management is the study of achievable rates within communication networks with no channel state information at the transmitter (CSIT) beyond knowledge of the network structure itself. In this paper, we consider topological interference management within the context of a two-cell two-user-per-cell interference broadcast channel (IBC) with alternating connectivity. Topological feedback, even though minimal, allows the transmitters to track the changing network topology and then exploit the varying connectivity states to obtain a degrees of freedom (DoF) gain. We derive novel outer bounds on the DoF achievable by the two-cell two-user-per-cell IBC with alternating connectivity. The analysis initially focuses on the single-input single-output (SISO) case and is later extended to multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems. While global channel knowledge is restricted to topological information only, varying degrees of local CSIT availability are considered, depending on the network configuration. Additionally, we investigate the achievability of the derived bounds and for the case where all alternating connectivity states are equiprobable propose new transmission schemes based on joint coding across states.

In this paper, we use stochastic geometry to characterize spatially distributed multi-antenna users within a cell that consists of a single multiple-input multiple-output (MIMO) base station (BS) equipped with a large antenna array. We also use large dimensional random matrix theory (RMT) to achieve deterministic approximations of the sum rate of this system. In particular, we consider the users inside the cell to follow a Poisson point process (PPP). The sum rate of this system is analyzed with respect to (i) the different number of antennas at the BS as well as (ii) the intensity of the users within the coverage area of the cell. We obtained closed-form approximations for the deterministic rate at low signal-to-noise ratio (SNR) and high SNR regimes, which have very low computational complexity. We also derive the deterministic rate corresponding to a general user who is chosen from a set of users ordered in accordance with PPP.

This paper investigates the optimization of the generalized likelihood ratio test (GLRT) eigenvalue-based spectrum sensing detector in terms of decision thresholds and sensing time. In order to guarantee the interests of primary and secondary users simultaneously, the sensing performance is assessed using the total error rate, i.e., the summation of probabilities of false alarm and missed detection. Therefore, the generalized statistical distributions of the test statistic are derived under the absence and presence of primary users, assuming an arbitrary number of receive antennas. These distributions are necessary for the analyses of the total error rate performance and the optimization. The optimization consists of two parts. Firstly, the optimal decision threshold is numerically obtained, which can minimize the total error rate under the constraints of target probabilities of false alarm and missed detection. Secondly, the optimal sensing time is obtained when a target total error rate is guaranteed, so that the spectrum sensing process can be accelerated without the loss of sensing accuracy. Furthermore, the simulation and theoretical results reveal that the chosen optimal decision thresholds benefit the primary and secondary users simultaneously and the chosen optimal sensing time improves the speed of spectrum sensing.

In this study, the authors investigate the Gallager's error exponents of dual‐hop amplify‐and‐forward systems over generalised η ‐ μ and κ ‐ μ fading channels, two versatile channel models which encompass a number of popular fading channels such as Rayleigh, Rician, Nakagami‐ m , Hoyt and one‐sided Gaussian fading channels. The authors present new analytical expressions for the probability density function of the end‐to‐end signal‐to‐noise‐ratio (SNR) of the system. These analytical expressions are then applied to analyse the system performance through the study of Gallager's exponents, which are classical tight bounds of error exponents and present the tradeoff between practical information rate and the reliability of communication. Two types of Gallager's exponents, namely, random coding error exponent and expurgated error exponent, are studied. Based on the newly derived analytical expressions, the authors provide an efficient method to compute the required codeword length to achieve a predefined upper bound of error probability. In addition, the analytical expressions are derived for the cutoff rate and ergodic capacity of the system. Moreover, simplified expressions are presented at the high SNR regime. All the analytical results are verified via Monte–Carlo simulations.

In this work we consider the multiple-input multiple-output (MIMO) interference broadcast channel (IBC) and analyse the performance of interference alignment (IA) under imperfect channel state information (CSI), where the variance of the CSI error depends on the signal-to-noise ratio (SNR). First, we derive an upper bound on asymptotic mean loss in sum rate compared to the perfect CSI case and then we quantify the achievable degrees of freedom (DoF) with imperfect CSI. Both sum rate loss and achievable DoF are found to be dependent on the number of cells in the system and the amount of users per cell, in addition to the CSI error parameters themselves. Results show that when error variance is inversely proportional to SNR, full DoF are achievable and the asymptotic sum rate loss is bounded by a derived value. Additionally if the CSI imperfection does not disappear for asymptotically high SNR, then the full DoF gain promised by IA cannot be achieved; we quantify this loss in relation to the CSI mismatch itself. The analytically derived bounds are validated via system simulation, with the cellular counterparts of the maximum signal-to-interference-plus-noise ratio (Max-SINR) and the minimum weighted leakage interference (Min-WLI) algorithms being the IA techniques of choice. Secondly, inspired by the CSI mismatch model used to derive the bounds, we present a novel Max-SINR algorithm with stochastic CSI error knowledge (Max-SINR-SCEK) for the MIMO IBC. Simulations show that the proposed algorithm improves performance over the standard one under imperfect CSI conditions, without any additional computational costs.

In this paper, the multi-way relaying scenario is considered with M users who want to exchange their information with each other with the help of N relays (N ≫ M) among them. There are no direct transmission channels between any two users. Particularly, all users transmit their signals to all relays in the first time slot and M - 1 relays are selected later to broadcast their mixture signals during the following M - 1 time slots to all users. Compared to the transmission with the help of single relay, the multi-way relaying scenario reduces the transmit time significantly from 2M to M time slots. Random and semiorthogonal relays selections are applied. Rician fading channels are considered between the users and relays, and analytical expressions for the outage probability and ergodic sum rate for the proposed relaying protocol are developed by first characterizing the statistical property of the effective channel gain based on random relays selection. Also, the approximation of ergodic sum rate at high signal-to-noise ratio regime is derived. In addition, the diversity order of the system is investigated for both random and semiorthogonal relay selections. Meanwhile, it is shown that when the relays are randomly separated into L groups of M - 1 relays, the group with maximum average channel gain can achieve the diversity order L, which will increase when more relays considered in the scheme. Furthermore, when semiorthogonal selection (SS) algorithm is applied to select the relays with semiorthogonal channels, it is shown that the system will guarantee that all the users can decode the others information successfully. Moreover, the maximum of channel gain after semiorthogonal relays selection is investigated by using extreme value theory, and tight lower and upper bounds are derived. Simulation results demonstrate that the derived expressions are accurate.

Electronically steerable parasitic array radiator (ESPAR) antenna has been proposed to obtain multiple antenna functionality with only a single radio frequency (RF) chain. However, for some signals, the input resistance of the ESPAR antenna (EA) becomes negative. A negative input resistance would lead to oscillatory/unstable behavior of an EA to transmit signals. In this work, we address this issue of an EA by obtaining approximate signals for transmission, which are close to the ideal signals in the mean-squared-error (MSE) sense, and satisfy the requirement that the input resistance is positive. Specifically, we formulate and solve an optimization problem to minimize the MSE between the ideal and the approximate signals taking into account the constraint on the input resistance. Closed-form expressions to calculate the approximate signal vector from ideal signal vector are also obtained, resulting in simplified processing at the transmitter. We denote the EA utilizing the novel closed-form expressions as EA with preprocessing (EA-P) and the EA without any preprocessing as the standard EA (EA-S). The performance of EA-P is compared with the performance of EA-S and the standard multiple antenna system, with multiple RF chains, under various communication scenarios. Our simulations show that the performance of EA-S significantly degrades compared with the standard multiple antenna system and an error floor is obtained. However, using the proposed EA-P scheme, the error floor is avoided and nearly the same performance as that of the standard multiple antenna system is achieved.

Delayed channel state information at the transmitter (CSIT) due to time variation of the channel, coming from the users' relative movement with regard to the BS antennas, is an inevitable degrading performance factor in practical systems. Despite its importance, little attention has been paid to the literature of multi-cellular multiple-input massive multiple-output (MIMO) system by investigating only the maximal ratio combining (MRC) receiver and the maximum ratio transmission (MRT) precoder. Hence, the contribution of this work is designated by the performance analysis/comparison of/with more sophisticated linear techniques, i.e., a minimum-mean-square-error (MMSE) detector for the uplink and a regularized zero-forcing (RZF) precoder for the downlink are assessed. In particular, we derive the deterministic equivalents of the signal-to-interference-plus-noise ratios (SINRs), which capture the effect of delayed CSIT, and make the use of lengthy Monte Carlo simulations unnecessary. Furthermore, prediction of the current CSIT after applying a Wiener filter allows to evaluate the mitigation capabilities of MMSE and RZF. Numerical results depict that the proposed achievable SINRs (MMSE/RZF) are more efficient than simpler solutions (MRC/MRT) in delayed CSIT conditions, and yield a higher prediction at no special computational cost due to their deterministic nature. Nevertheless, it is shown that massive MIMO are preferable even in time-varying channel conditions.

A selective vector perturbation technique is introduced for low-power Small Cell downlink. In contrast to conventional vector perturbation (VP) where the search for perturbation vectors involves all users' symbols, here the perturbation is applied to a subset of the transmitted symbols. This therefore introduces a performance-complexity tradeoff, where the complexity is greatly reduced compared to VP by limiting the dimensions of the sphere search, at the expense of a performance penalty compared to VP. By changing the size of the subset of perturbed users, the above tradeoff can be controlled. We further propose three distinct criteria for selecting which users' symbols to perturb, each of which yields a different performance-complexity tradeoff. The presented analytical and simulation results show that the proposed is most useful in the low-power small cell scenarios where power efficiency levels improved by up to 300% compared to VP are demonstrated.

A vector perturbation (VP) scheme is proposed for the downlink of multi-user multiple input multiple output (MU-MIMO) systems with limited feedback. Instead of a computationally expensive sphere search used in conventional VP, the proposed scheme uses a MinMax Optimization to select the perturbation quantities. In addition, the proposed VP circumvents the need for receive-scaling by constraining the search of perturbing vectors to the area in the symbol constellation which is constrictive to the information symbols, i.e. the area where the distances from the decision thresholds are increased with respect to a distance threshold. Consequently, while conventional VP requires the feed-forwarding of the scaling factor to the receiver for correct detection, the proposed scheme does not require the scaling of the received symbols. This advantage is particularly pronounced in limited feedback scenarios where the scaling factors forwarded to the receiver are prone to quantization errors. As illustrated by the results, the error floor encountered in conventional VP in limited feedback scenarios is avoided in the proposed scheme.

With the presence of perfect channel state information (CSI), the achievable degrees of freedom (DoF) in wireless interference networks can be linearly scaled up with the number of users. Achievability is based on the idea of interference alignment (IA). However, with the presence of imperfect CSI, the sum rate becomes degraded and full DoF may not be achievable anymore. In this paper and by considering a generalized CSI mismatch model, we propose a novel MMSE-based IA scheme such that the unitary beamformers are adaptively designed to achieve better performance when only imperfect CSI is available. We then compare the performance of the proposed scheme with maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that while under perfect CSI the proposed algorithm achieves the same performance as Max-SINR, the former outperforms the latter under CSI mismatch. Meanwhile, it is shown that the proposed algorithm needs less CSI to be available and has less computational complexity compared to Max-SINR.

This paper investigates optimization of the sensing threshold that minimizes the total error rate (i.e., the sum of the probabilities of false alarm and missed detection) of eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. Four techniques are investigated, which are maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME) detection, energy with minimum eigenvalue (EME) detection, and the generalized likelihood ratio test (GLRT) detection. The contribution of this paper is of four parts. Firstly, we present the derivative of the matrix-variate confluent hypergeometric function, which is required for the MED case. Secondly, we derive the probabilities of false alarm for both cases MME and EME detection. Thirdly, we derive the probability of missed detection for the GLRT detector. Finally, we provide the exact expressions required to obtain the optimal sensing thresholds for all cases. The simulation results reveal that for all the investigated cases the chosen optimal sensing thresholds achieve the minimum total error rate.

We consider a realistic cellular multi-user uplink channel with an excess of base station (BS) antennas, where the number of BS antennas and the number of users per cell increase at the same rate. Specifically, we investigate the negative impact of delayed channel state information at the transmitter (CSIT), when a minimum-mean-square-error (MMSE) detector is applied. Nevertheless, channel prediction is used for overcoming delayed CSIT degradation. We provide the asymptotic signal-to-interference-plus-noise ratios (SINRs) that demonstrate not only their dependence on delayed and predicted CSIT, but also the outperformance of MMSE against maximal ratio combiner (MRC). The deterministic nature of the results renders them easily computed, while simulations show their accuracy even for practical system dimensions.

With interference alignment (IA), the achievable degrees of freedom (DoF) in wireless networks can be linearly scaled up with the number of users. However, to attain full DoF, the availability of perfect network channel state information (CSI) is mandatory, which impedes the practical deployment of IA since only partial network CSI may be accessible. In this paper, we investigate the effect of CSI mismatch on the performance of maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that while with perfect CSI, Max-SINR outperforms interference leakage minimization algorithms, with the presence of CSI mismatch, its comparative improvement becomes negligible. We then propose an adaptive Max-SINR which can notably improve the performance of original Max-SINR under CSI mismatch.

We propose a performance-complexity tradeoff for vector perturbation (VP) precoding in the downlink of multiuser multiple input multiple output (MU-MIMO) systems, that bridges the gap between linear and non-linear channel-inversion type precoding. To this end, we introduce a VP design that applies a performance-determined threshold to the desired norm of the preceded signal, to reduce the search through candidate perturbation vectors by the sphere encoder. Once this threshold is met, the search for the perturbation vectors finishes thus saving significant complexity at the transmitter. Towards future largescale MIMO systems, we test t he proposed tradeoff in systems with increasing transmit antennas is fixed physical space. While it is known that linear precoding becomes near-optimal in the massive MIMO region when ignoring transmit correlation, a) we show that t here still remains a performance gap between linear and non-linear precoding once realistic antenna array deployment is considered and b) we utilize the proposed scalable approach to bridge this gap. The presented analysis and results show that t he sum rates achieved are within 90% of those for conventional VP at less than half the computational complexity.

Detection of primary users is a very crucial task for cognitive radio networks. On the other hand, the choice of the spectrum sensing algorithm affects the achievable throughput of the secondary network when the cognitive radios employ the interweave approach. Focusing on the eigenvalue-based detector, it can be seen that most proposed methods are based on time domain. Therefore, in this paper we present and analyse a new class of eigenvalue detectors in frequency domain (FD). The major contributions of this paper are of two parts. First, we introduce a new minimum-maximum eigenvalue (MME) spectrum sensing method based on Bartlett's method of estimation. By making use of the eigenvalues of the diagonalized quadratic form representation of Bartlett's estimate, the distribution of the ratio of extreme eigenvalues is studied, and then the performance of the detector is addressed and accurate expressions where obtained for the probabilities of false alarm and detection. Second, assuming that the secondary network employs an interweave approach we study the average achievable throughput. All obtained formulas are verified through Monte Carlo simulations. The obtained results gives an insight into the validity of using MME detection in FD.

With the knowledge of both channel and data information at the base station prior to downlink transmission, we can increase the received signal-to-noise ratio (SNR) of each user without the need to increase the transmitted power. Achievability is based on the idea of phase alignment (PA) precoding where instead of removing the destructive interference, it judiciously rotates the phases of the transmitted symbols. In this way, for each user, the received interference from the other users add up coherently, and consequently we can glean higher received SNRs at all mobile terminals. In addition, it is well-known that the regularized channel inversion (RCI) improves the performance of channel inversion (CI). In line with this and similar to the RCI precoding, in this paper we propose the idea of regularized PA (RPA) which is shown to improve the performance of original PA precoding. To do so, we first rectify the original PA precoding by deriving a closed-form expression of its scaling factor. We then use this new analysis to select an appropriate regularization factor for the proposed RPA scheme. Finally, we drive an explicit formula regarding its received SNR. Since the focus of this work is on linear precoders, we show that the proposed RPA precoding outperforms CI, RCI, and PA precoders from both symbol-error rate (SER) and sum rate perspectives. We also consider the performance of RPA under imperfect channel state information at transmit side. We show that even in this case, RPA precoding is as sensitive as other linear precoders to channel imperfections.

In this work we investigate the degrees of freedom (DoF) performance of the multiple-input multiple-output (MIMO) interference channel (IC) with limited channel state information (CSI) feedback. We generalise two space-time interference alignment (STIA) algorithms to the K user MIMO IC with a transmit power constraint and show how these schemes exploit both current and outdated CSI to achieve an improved DoF performance. We show that by combining the STIA schemes with traditional methods major DoF gain can be achieved for a variety of limited CSI feedback scenarios in comparison to what would be obtained via the use of the traditional techniques on their own. In particular we prove that optimal DoF can still be achieved in situations where current CSI is unavailable for a derived fraction of the time. Finally we validate the promised DoF results via system simulation and show how these DoF gains reflect in terms of sum rate achievable.

Massive Multiple-Input-Multiple-Output (MIMO) systems deploying a large number of antennas at the base station (BS) have been shown to produce high spectral and energy efficiencies (EE) under the assumptions of increasing BS physical space and critical antenna spacing. We propose a more realistic system model considering a fixed physical space: incorporating coupling and correlation among the BS antennas while providing a realistic analysis of the power consumption using a new power consumption model, taking into account the circuit power consumptions as a function of the number of BS antennas. We also touch on the performance analysis of two practical low complexity detectors keeping EE into consideration. The simulation results obtained show that EE does not monotonically increase with the number of BS antennas. On the contrary, it is a decreasing concave or quasi concave function of the number of BS antennas depending on the detection technique used at the receiver. Also shown is that with decreasing spacing between the antennas, mutual coupling increases contributing towards reduction in EE. Our analysis thus shows that EE does not increase in a massive MIMO system when a large number of antennas are to be accommodated within a fixed physical space and the total power consumed is considered to be a function of the antennas.

Interference alignment (IA) is a transmission technique for exploiting all available degrees of freedom (DoF) in the frequency- or time-selective interference channel with an arbitrary number of users, which can achieve linear capacity scaling with number of users. However, standard IA approach has limit performance in the low-to-moderate signal-to-noise ratio (SNR) region. Recently, linear combination designs have been proposed to improve performance of sum rate at finite SNR which jointly considers the interference and the signal optimization simultaneously, but is sensitive to the weight selection. Therefore, it motivates us to propose a normal-boundary intersection (NBI)-based design that jointly optimizes the rank of interference and its power with evenly spread parameters. The underlying problem is transferred into limited subproblem that can be efficiently solved. Simulation results validate the effectiveness of the proposed algorithm that achieves the Pareto optimality and provides evenly-distributed Pareto frontiers.

Correlation between the legitimate receiver and the eavesdropper has been seldom considered in the literature when evaluating secrecy metrics in stochastic wireless networks. In practice, however, poor scattering conditions may lead to spatially correlated channels, which can be exploited by eavesdroppers. In this paper we investigate the connection outage and secrecy outage in Poisson-distributed random networks under Nakagami-m fading and mutually correlated legitimate and eavesdropping channels. Numerical results show that correlated fading has an important effect on security, which may be either beneficial or harmful, depending on the secrecy outage constraints.

Two-tier heterogeneous wireless networks are considered in this paper where nodes in the first tier are distributed as a Poisson Point Process (PPP). Nodes in the second tier are distributed as a Poisson Clustered Process (PCP). Nodes in the second tier have imperfect channel state information (CSI) of the first tier node whose Voronoi cell they are in. On one hand, cross-tier interference is coordinated to the second tier nodes by interference alignment (IA) approach, where we strike a balance between increasing the number of data streams and increasing signal-to-interference (SIR) ratio at each data stream. On the other hand, the remaining interference is modelled by stochastic geometry and analytic expressions of throughput are derived. Monte Carlo simulations validate our expressions and show the gain brought by the interference coordination approach.

This work studies the uplink of a cellular network with zero-forcing (ZF) receivers under imperfect channel state information at the base station. More specifically, apart from the pilot contamination, we investigate the effect of time variation of the channel due to the relative users' movement with regard to the base station. Our contributions include analytical expressions for the sum-rate with finite number of BS antennas, and also the asymptotic limits with infinite power and number of BS antennas, respectively. The numerical results provide interesting insights on how the user mobility degrades the system performance which extends previous results in the literature.

In the multiantenna downlink and under the availability of perfect channel state information (CSI) at base station (BS), regularized channel inversion (RCI) outperforms plain channel inversion (CI). Nevertheless, in the presence of imperfect CSI at BS, since RCI is more sensitive than CI to CSI imperfections, the performance of RCI becomes more degraded than that of CI. Therefore, in this paper, we propose an adaptive RCI technique which tries to compensate the degraded performance of standard RCI compared to CI when only imperfect CSI is available at BS. We do so by deriving an appropriate regularization parameter as a function of channel estimation error variance, which is possible to be known in advance. We also derive the output signal-to-interference-plus-noise ratio (SINR) of each user and show that the adaptive RCI is a generalized version of standard RCI such that by setting the error variance equal to zero, the former boils down to the latter. Simulation results certify that the proposed scheme results in improved bit error rates (BER) and higher achievable sum rates compared to standard RCI.

In multiantenna downlink, linear precoders like channel inversion (CI) are more desirable than their nonlinear counterparts due to their reduced complexity. However, to harness the full capabilities of multiuser multiantenna downlink, the availability of perfect channel state information (CSI) at base station (BS) is mandatory. Since from the practical point of view, this is an optimistic assumption, in this paper, we evaluate the asymptotic performance of CI under a generalized CSI mismatch model where the variance of the channel estimation error depends on the signal-to-noise ratio (SNR). In this case, we quantify novel bounds regarding the asymptotic mean loss in sum rate and achievable degrees of freedom (DoF) by deriving the received signal-to-interference-plus-noise ratio (SINR) of each user. It is shown that, for example, the achievable DoF is directly related to the SNR exponent of the channel estimation error variance. In other words, if the intention is to keep the asymptotic mean loss in sum rate bounded, the variance of the channel estimation error must at least scale with the inverse of SNR. Also an asymptotic gap to capacity for analog feedback is derived.

In wireless interference networks, orthogonal medium access techniques like time division multiple access (TDMA) and frequency division multiple access (FDMA) achieve merely one degree of freedom (DoF). However, by using interference alignment (IA) the achievable DoF can be linearly scaled up with the number of users. Nevertheless, this outperformance of IA heavily depends on the availability of perfect channel state information (CSI), which is not a realistic assumption in practice. Since under imperfect CSI, the performance of IA may become severely degraded, design of enhanced IA algorithms by relying on the availability of merely imperfect CSI is of particular interest. In this paper, we propose a least squares (LS)-based IA algorithm which adaptively designs the beamformers based on the knowledge of the channel estimation error variance, which is possible to be known in advance. Then, we compare the performance of the proposed scheme with interference leakage minimization algorithms. It is shown that under both perfect and imperfect CSI, the proposed LS-based IA outperforms interference leakage minimization algorithms.

In this paper, we study the degrees of freedom (DoF) of the two-user time-correlated multiple-input-multiple-output (MIMO) interference channel (IC), under realistic assumptions. In particular, the transmitters have imperfect knowledge of the current and the delayed channel state information (CSI). The novelty of this study relies upon the fact that this is the first time, within the literature of IC, that imperfect CSI is addressed for such a case. The delayed CSI at the transmitter (CSIT) is assumed to be more accurate than the current value. We identify the DoF region, which provides an insight on the behaviour of the DoF as a function of the varying qualities of the current and the delayed channel. It is also worth mentioning that any knowledge of imperfect delayed CSIT can also be utilized. Furthermore, an achievability scheme is proposed for each vertex in DoF region. Finally, simulation of the proposed scheme verifies our results.

The ergodic channel capacity (ECC) of single-branch receivers is studied under the scenarios described by means of α-η-μ, α-κ-μ, and α-λ-μ-η generalized fading channels. Novel expressions are derived, which are the most general in this scientific area. Moreover, it is shown that, for any given fading condition, the α-μ ECC divides the fading plane in two regions of capacity, appearing as either lower or upper bound in the α-η-μ and α-κ-μ fading environments. Numerical results are presented to illustrate the proposed mathematical analysis and to examine the effects of the fading severity on the concerned quantities.

Certain practical limitations, such as finite CSI feedback delay, make the knowledge of instantaneous perfect CSI impossible and bring the term of delayed CSIT to the forefront. In this paper, it is described how both current and delayed CSI could be exploited by generalizing the space-time interference alignment transmission algorithm (STIA) to the K (K ≥ 3) user M × N interference channel. Specifically, the degrees of freedom (DoF) gain is characterized as a function of the CSI feedback delay γ and the system parameters (K, M, N). Surprisingly, the DoF become optimal, i.e., no loss is achieved with respect to the case of perfect current CSIT, as far as the normalized CSI feedback delay is less than a specific value dependent on the number of users, and the number of transmit antennas equals to N(K - 1). The proposed algorithm reveals unprecedented properties characterizing the performance of the system by providing the limits of the multiplexing gain with relation to the feedback time delay.

We consider a multi-cell multi-user downlink channel of a time-division duplex (TDD) MIMO system, where the base stations (BSs) employ the concept of massive MIMO, i.e., they are equipped with a large number of antennas. In addition, the number of users increases with the same speed. Focusing on the practical impairments of the channel such as pilot contamination and, in particular, delayed channel state information at the transmitter (CSIT), we derive an approximation of the sum rate with regularized zero-forcing (RZF) precoding, which provides a quantification of the capacity loss. As a result, it is deemed necessary to obtain the deterministic equivalent sum rate by incorporating in our analysis channel prediction circumventing the degradation due to delayed CSIT. The proposed results are accurate for realistic system dimensions, as simulations testify. Finally, we show the benefits of applying RZF in the sum rate against using eigenbeamforming (BF) for the same Doppler shift with no extra computational complexity.

Interference alignment (IA) is potentially able to deliver more than one degree of freedom (DoF) in wireless networks such that the achievable DoF can be linearly scaled up with the number of users. This improvement, however, comes at the cost of availability of perfect channel state information (CSI) which hinders the practical implementation of IA since only partial CSI may be accessible. In this paper, we quantify the performance of IA under CSI imperfections where the variance of the CSI measurement error depends on the signal-to-noise ratio (SNR). We show that when this error variance is proportional to the inverse of SNR, full DoF is attainable. In this case, an upper bound on asymptotic mean loss in sum rate compared to the perfect CSI case is derived. Furthermore, we also derive a tight lower bound on the achievable DoF when the error variance is proportional to the inverse of SNR to a power of a constant. It is shown that when this constant is bounded between zero and one, a fraction of the total DoF is achievable. Using numerical simulations, we substantiate the analytically derived bounds.

In this paper, we investigate the error exponents of dual-hop amplify-and-forward (AF) system for η-μ fading channel. Channel capacity of a wireless communication system gives only the knowledge of maximum achievable rate. Therefore, it is necessary to analyse the decoding complexity of the code that achieves a certain level of reliable communication. In fact, a measure of reliability called error exponent exists which sets ultimate bounds on the performance of communication systems employing codes of finite complexity. Assuming the receiver has full channel state information (CSI) and the transmitter has no CSI, we derive the novel exact expressions of Random coding error exponent (RCEE) and expurgated error exponent which provide insight into an elementary tradeoff between the communication reliability and information rate. Moreover, the necessary codeword length can be computed easily without the extensive Monte-Carlo simulation to achieve predefined error probability at a given rate. Meanwhile, simplified approximate expressions in the high signal-to-noise ratio (SNR) regime are also obtained. In addition, we derive the exact closed-form expressions for the ergodic capacity and cutoff rate.

In a K ‐user multiple‐input multiple‐output (MIMO) interference channel where each N ‐antenna transmitter communicates with its corresponding M ‐antenna receiver by using d degrees of freedom (DoF), the feasibility condition for conventional interference alignment (IA) implies that M + N > d(K + 1). In this paper, we consider a K ‐user MIMO interference channel where averagely half of the total decoded data can be shared by receive nodes via partial coordination. We propose IA algorithms such that first, their feasibility condition can now be expressed as M + N > d(K + 4)/2, which further implies less number of antennas is needed in comparison with conventional IA techniques to achieve the same number of DoF; and second, even with this reduced number of antennas, their throughput is still comparable to that of conventional IA methods. This is particularly pronounced for asymptotically large K where the required number of antennas for the proposed IA schemes can be half of that of conventional IA techniques to secure the same number of DoF. Moreover, we also examine the performance of the proposed IA algorithms in the presence of both error propagations and channel estimation errors. Simulation results show that in these cases, the throughput of the proposed algorithms can be comparable to that of conventional IA techniques.

The authors present a beamforming scheme with opportunistic relaying (namely opportunistic beamforming) for wireless security under amplify‐and‐forward (AF) and decode‐and‐forward (DF) strategies. The relay selection is performed using the method of distributed timers, where all the relays use their timers to estimate own instantaneous channel gains and compete to access the wireless medium according to their own channel conditions. The performance of opportunistic beamforming scheme in terms of secure outage probability is analysed and the beamforming problem as a semidefinite programming problem with its optimisation framework is formulated. The results show that, in an opportunistic beamforming scheme, competition among cooperative relays offers diversity benefits in the direction of destination that enhances secrecy rate (i.e. minimises secure outage probability) and adhere to the ‘opportunistic’ cooperation rule giving priority to the ‘best’ available relay even when they are not chosen to transmit but rather chosen to cooperatively listen. Opportunistic beamforming scheme with DF strategy enhances secrecy rate than the beamforming with multiple DF relays while in the case of AF strategy, it provides significant improvement in the secrecy rate compared to the opportunistic relaying, the equal‐power multiple‐relay transmission and the single‐relay transmission schemes.

We propose an energy-efficient vector perturbation (VP) technique for the downlink of multiuser multiple-input-single-output (MU-MISO) systems. In contrast to conventional VP where the search for perturbation vectors involves all users' symbols, here, the perturbation is applied to a subset of the transmitted symbols. This, therefore, introduces a performance-complexity tradeoff, where the complexity is greatly reduced compared to VP by limiting the dimensions of the sphere search, at the expense of a performance penalty compared to VP. By changing the size of the subset of perturbed users, the aforementioned tradeoff can be controlled to maximize energy efficiency. We further propose three distinct criteria for selecting which users' symbols to perturb, each of which yields a different performance-complexity tradeoff. The presented analytical and simulation results show that partially perturbing the data provides a favorable tradeoff, particularly at low-power transmission where the power consumption associated with the signal processing becomes dominant. In fact, it is shown that diversity close to the one for conventional VP can be achieved at energy efficiency levels improved by up to 300% compared to VP.

This paper presents an analytical investigation on the performance of Rayleigh-product MIMO channels with linear minimum mean-square-error (MMSE) or zero-forcing (ZF) receivers. For MMSE receivers, exact closed-form expressions for the ergodic sum-rate of the system are derived. In addition, simplified expressions are obtained for the key parameters dictating the sum-rate performance of the system in the high signal-to-noise ratio (SNR) regime (i.e., high SNR slope and power offset) and low SNR regime (i.e., minimum energy per information bit required to convey any positive rate and the wideband slope). While for ZF receivers, tight closed-form upper and lower bounds for the ergodic sum-rate of the system are derived. It is analytically proven that the ZF and MMSE receivers achieve the same sum rate performance in the high SNR regime. Moreover, for both MMSE and ZF receivers, the achievable diversity-multiplexing tradeoff (DMT) of Rayleigh-product MIMO channels is characterized. The findings suggest that a larger number of scatterers will improve the the performance of Rayleigh-product MIMO channels with linear receivers, and the ZF receivers achieve the same performance as the MMSE receivers in Rayleigh-product MIMO channels in the high SNR regime. Moreover, it is demonstrated that as long as the number of the scatterers is greater than the number of receive antennas, linear receivers achieve the optimal DMT.

Vector precoding (VP) requires the feed-forwarding of the transmit scaling factor to the receiver for correct detection. This can be problematic in fast fading scenarios where the statistics of the scaling factor change frequently and in limited feedback scenarios where the feed-forwarding to the receiver is prone to quantization errors. In response to this, a new VP scheme is proposed for the downlink of multi-user multiple input multiple output (MU-MIMO) systems with limited feedback. The proposed VP circumvents the need for receive-scaling by constraining the search of perturbing vectors to the area in the symbol constellation which is constrictive to the information symbols, i.e. the area where the distances from the decision thresholds are increased with respect to a distance threshold. By doing this, the perturbation quantities need not be removed at the receiver and successful detection can be done without the use of the modulo operation and the scaling factor. In addition, instead of a computationally expensive sphere search used in conventional VP, the proposed scheme uses a MinMax Optimization to select the perturbation quantities. As illustrated by the analysis and results, the error floor encountered in conventional VP in limited feedback scenarios is avoided in the proposed scheme.

We propose a low-complexity vector precoding (VP) scheme for the downlink of multi-user multiple input multiple output (MU-MIMO) systems. Instead of performing a full sphere search to maximize the receive signal to noise ratio (SNR), the search for the perturbation vectors finishes once a threshold SNR value is reached, thus saving significant computational burden at the transmitter. This threshold is determined by the quality of service (QoS) requirements of the mobile users. To evaluate the advantages of the proposed technique compared to VP, we analytically calculate its computational complexity in terms of the volume of the associated search space. The results show that the proposed thresholded VP (TVP) offers a significantly reduced complexity compared to VP.

It has been conjectured by Høst-Madsen and Nosratinia that the K-user single-input single-output (SISO) complex Gaussian interference channels with constant channel coefficients have merely one degree of freedom (DoF) regardless of the number of users, i.e., K. Then, Cadambe and Jafar introduced the idea of interference alignment (IA) being able to achieve K/2 DoF in time-varying SISO interference channels. Moreover, their joint work with Wang settled the Høst-Madsen-Nosratinia conjecture in negative by using the idea of asymmetric complex signaling to achieve 1.2 DoF for K-user constant SISO interference channels. In this paper, a linear IA scheme for K-user constant SISO interference channels is proposed which could enable us to achieve K/4 DoF for almost all channel coefficients. This means that whenever K ≥ 5, the proposed scheme could achieve at least 1.25 DoF. The main idea of the proposed method relies on the linear IA using symbol extension by Cadambe-Jafar which is not effective for constant channels. However, we show that along with signal rotation across every two consecutive time slots to artificially build a random time-varying channel out of a constant channel, the proposed method can be directly applied to constant channels to achieve K/4 DoF.

This paper considers a K-user multiple-input multiple-output (MIMO) interference channel in which uncoordinated interference appears. Due to the uncoordinated interference, perfect interference alignment (IA) may be not attained, which indicates the interference subspaces can not be completely aligned. The rank constrained rank minimization (RCRM) framework has been recently developed to minimize the rank of the subspace spanned by interference signals with full rank constraint on the direct signal space. To solve this non-convex and intractable problem, we introduce a log-sum function as an approximation surrogate and develop a joint Frobenius norm and reweighted nuclear norm approach which jointly enhances the sum rate at low-to-moderate signal-to-noise ratio (SNR) and the achievable multiplexing gain per user in the high SNR regime. The optimum solutions are iteratively achieved with the convergence guaranteed. Simulation results are presented to validate the effectiveness of the proposed reweighted nuclear norm algorithm and its further development.

In this work, we introduce multiple-input-multiple-output (MIMO) interference alignment (IA) in an homogeneous and asynchronous ad hoc network. Perfect channel state information and working status of nodes are conveyed by instantaneous feedback link to one-hop neighbors. Transmitters align their interference to receivers and receivers eliminate interference by zero-forcing method asynchronously. The feasibility conditions for IA are considered as a critical factor to the performance, and the situations are divided according to whether the feasibility condition can be satisfied or not. We derive closed-form expressions for the upper and lower bounds on outage probability and transmission capacity in both cases. Numerical results show that with larger path loss exponent and number of antennas, the performance increases because a greater proportion of the interference can be eliminated.

We investigate he performance-complexity tradeoff for vector perturbation (VP) precoding in he downlink of multiuser multiple input multiple output (MU-MIMO) systems. To his end, we introduce a VP design ha applies a performance-determined threshold o he desired norm of he preceded signal, o reduce he search through multiple candidate perturbation vectors by he sphere encoder. Once his threshold is me, the search for the perturbation vectors finishes thus saving significant computational burden at the transmitter. Contrary o conventional VP which performs a compuationally intense sphere search to find the absolute minimum of the transmit signal norm, he proposed scheme can trade off error rate performance for a much reduced complexity of precoding. The presented analysis and results show ha he proposed thresholded VP (TVP) offers a complexity reduction of up o 90% in a 4 × 4 and 99% in a 10 × 10 MIMO, for a moderately increased error rate.

We consider the problem of secret communication through co-existing radio systems assisted by cognitive relay (CR). Assuming a cognitive radio setup in which secondary base station (SBS) is allowed to transmit simultaneously with the primary base station (PBS) over the same channel, at first, we investigate the impact of interferences on the receive diversity of cognitive interference channels and quantify the loss of receive diversity order as well as the secrecy rate due to interferences. Then, we propose a scheme to improve the secrecy rate of secondary receiver (SR) making use of interference energy that already exists in the communication medium employing selective precoding at the CR. In the proposed scheme, interference provides an additional source of energy that enhances secrecy rate at the SR without the need to increase the transmitted power. We also calculate the secrecy rate of primary receiver (PR) in order to focus the performance of proposed scheme in enhancing security of the cognitive interference channels. Our results show that exploiting free interference power, the performance of secondary downlink can be improved without affecting the performance of PR.

Along with the channel capacity, the error exponent is one of the most important information-theoretic measures of reliability, as it sets ultimate bounds on the performance of communication systems employing codes of finite complexity. In this paper, we derive the closed-form expressions for the Gallager's random coding and expurgated error exponents for Rayleigh fading multi-keyhole multiple-input multiple-output (MIMO) channels, which provides insight into an elementary tradeoff between the communication reliability and information rate. Moreover, we can easily compute the necessary codeword length without the extensive Monte-Carlo simulation to achieve predefined error probability at a given rate. In addition, we derive the exact closed-form expressions for the ergodic capacity and cutoff rate based on the easily computable Meijer G-function. We also quantify the effects of the number of antennas, channel coherence time and the number of keyholes on the required codeword length to achieve a certain decoding error probability.

This paper considers the spectrum sharing multiple-input single-output (MISO) underlay cognitive radio network, in which multiple primary users (PUs) coexist with multiple secondary users (SUs). A weighted trade-off beamforming is designed to balance the minimum signal-to-interference-plus-noise ratio (SINR) of the SUs and the maximum interferences to the PUs under a limited transmit power constraint. When the perfect channel state information at transmitter (CSIT) is available, the multi-objective function is converted into an auxiliary parametric single-objective problem. The underlying problem is solved by using semidefinite programming (SDP) relaxation. Due to the inevitable CSIT errors, a robust design is developed to provide robustness against the worst-case errors. Simulation results show that the proposed weighted trade-off design has the ability to achieve the Pareto optimal points

In this paper, we investigate the ergodic sum rate of K fading MIMO channels with linear MMSE receiver, which is an analytically friendly fading model to describe both the small scale fading and shadowing. The exact closed-form expression of the ergodic sum rate was derived, which is applicable for arbitrary number of transmit and receive antennas and any signal to noise ratio (SNR) range. Moreover, simple expressions were derived for the ergodic sum rate in the high and low SNR regimes. The analytical results enable us to gain insights on how the key system parameters affect the ergodic sum rate of the system. Numerical results are presented and verified via Monte Carlo simulations.

We consider the two-user time correlated multiple-antenna interference channel (IC) under realistic conditions. Specifically, the transmitters have not only perfect delayed channel state information (CSIT), but also asymmetrically imperfect current CSIT. Delayed CSIT, met to cases of practical interest (certain feedback latency and limited quality), can still be useful as shown by Maddah-Ali and Tse. In parallel, the assumption of unequal prediction of current CSIT based on past samples across different links, conduces to the consideration of a more realistic scenario, where different links face different Doppler spread. The degrees of freedom (DoF) region of the IC under these general conditions is obtained and characterized. In particular, we investigate the effects of the asymmetry appearing to different links, such as how the feedback capability of one user affects the other. In addition, the achievability schemes are provided. Finally, Monte Carlo simulation in terms of the sum rate validates the theoretical results and provides deeper insight.

Interference alignment (IA) is a promising technique to achieve more than one degree of freedom in wireless interference networks. It has been shown that in a k-user multiple-input multiple-output (MIMO) interference channel where each N-antenna transmitter communicates with its intended M-antenna receiver by sending d independent data streams, the aggregate number of transmit and receive antennas should satisfy M + N ≥ d(K + 1). This impedes the practical implementation of IA since for large K or d, the required number of antennas for each transceiver pair grows excessively. On the other hand, coordinated multipoint transceivers are inherent parts of future wireless networks since they provide significant performance improvement in communication quality of interference-limited networks. While the performance of coordinated transmitters has been widely investigated in the literature, in this paper and by relying on coordinated receivers, we propose IA algorithms which simultaneously satisfy the following properties: 1) unlike the common assumption of full information exchange among nodes and owing to the partial coordination, averagely half of the total data and cross channel state information is needed to be exchanged among receive nodes, 2) the feasibility condition of the proposed IA algorithms can now be expressed as M + N ≥ d(K + 4)/2 which further implies that for asymptotically large K and to achieve the same number of degrees of freedom, the required number of antennas for proposed methods can be half of that of regular IA techniques, 3) even with this reduced number of antennas, the achievable sum rate of proposed schemes is still comparable to that of conventional IA methods.

We consider the problem of secret communication through cognitive relay assisted interference channels in which secondary user (SU) is allowed to transmit simultaneously with the primary user (PU) over the same channel instead of waiting for an idle channel which is traditional for a cognitive radio. We propose two cooperative jamming (CJ) schemes to improve the secrecy rate of cognitive interference channels, where the multiple antenna cognitive relay transmit weighted jamming signals to create additional interferences in the direction of eavesdropper with the purpose of confusing it. !n the first CJ scheme, transmitter has the knowledge of all the channel state information (CSI) including eavesdropper channel while in the second CJ scheme transmitter has no CSI of the eavesdropper channel. The proposed CJ schemes are designed to cancel out jamming interference at both the primary receiver (PR) and the secondary receiver (SR) maintaining interference at the PR under a certain threshold. CJ with full CSI enhances secrecy rate by employing zero forcing (ZF) precoding while CJ with partial CSI also combining with ZF precoding improves the secrecy rate by degrading the signal-to-interference plus noise ratio (SINR) at the eavesdropper. Our results show that a combined approach of ZF precoding with CJ scheme is more significant in improving secrecy rate of cognitive interference channels for both full CSI and partial CSI scenarios.

We consider a confidential communication through log-normal fading channel in which a single antenna transmitter communicates with a legitimate receiver in the presence of an eavesdropper. Employing maximal ratio combining (MRC) and equal gain combining (EGC) reception schemes at the legitimate receiver and eavesdropper, we find the closed-form expressions for the secrecy parameters, namely, the probability of non-zero secrecy capacity and the asymptotic secrecy capacity in terms of channel parameters such as correlation coefficient and the diversity order. We quantify the effect of diversity and antenna correlation and investigate, how the logarithmic standard deviation influences these effects of diversity and antenna correlation on the secrecy parameters. Moreover, as a result of obtaining closed-form expressions for the secrecy parameters, it is insightful to see how the channel parameters affect the security of lognormal fading channels.

The performance of ad‐hoc networks is greatly affected by interference, particularly interference from nearby nodes. Based on stochastic geometry, this work studies a form of multiple‐input–multiple‐output (interference alignment (IA) that eliminates interference from transmitters within a range and treats the remaining interference as a shot noise process. Adapting to the bursty nature of ad‐hoc network traffic, the authors introduce a novel distributed ad‐hoc network with renewal process, whereby cooperation between interferer and receiver is implemented in one‐way process, which results from the difficulties for the node to change the beamforming or receiving matrix whereas communicating with a proposed transmitter. In addition, this scheme takes advantage of IA, leaving the desired signal with higher degree of freedom (DoF) compared with the partially zero‐forcing method. Outage probability and transmission capacity are derived with and without Rayleigh fading. Simulation results show the effect of IA in ad‐hoc network, including the incremental in the DoF of the desired signal as time goes by. Monte Carlo simulations are implemented and show that IA outperforms successive interference cancellation by at least 10 dB in terms of the signal‐to‐interference ratio with large path‐loss exponent.

The authors propose a distributed robust joint signal and interference alignment design for multiple‐input–multiple‐output cognitive radio (CR) networks where single primary link coexists with multiple secondary links. Considering two practical challenges of interference alignment: imperfect channel state information (CSI) and finite signal‐to‐noise ratio, the proposed scheme aims to minimise both the leakage of interference signals and that of the desired signals, while maintaining interference to the primary user below a permissible level. Under the assumption of the ellipsoidal CSI uncertainties, the joint worst‐case optimisation problem is decomposed and reformulated as semi‐definite programming form by using S ‐lemma, orthogonal relaxation and semi‐definite relaxation. Simulation results verify the effectiveness of the joint design, and robustness of the worst‐case design against channel uncertainties.

The performance of single-cell distributed multiple-input multiple-output (D-MIMO) systems is not only affected by small-scale Rayleigh fading but also from large-scale fading and path-loss. In this paper, we elaborate on the sum rate of D-MIMO systems employing linear zero-forcing receivers, accounting for both large and small-scale fading effects, as well as spatial correlation at the transmit side. In particular, we consider the classical lognormal model and propose closed-form upper and lower bounds on the achievable sum rate. Using these bounds as a starting point, we pursue a "large-system" analysis and provide asymptotic expressions when the number of antennas at the base station (BS) grow large, and when the number of antennas at both ends grow large with a fixed and finite ratio. A detailed characterization in the asymptotically high and low signal to noise ratio regimes is also provided. An interesting observation from our results is that in order to maximize the sum rate, the RPs should be placed at unequal distances to the BS when they experience the same level of shadowing. The resulting closed-form expressions are compared with the corresponding results on MIMO optimal receivers.

Spectrum sensing for cognitive radio is studied, using an electronically steerable parasitic antenna receptor (ESPAR), which relies on a single RF front end, and therefore meets the demanding low cost, power and size requirements of modern wireless terminals. We develop a strategy whereby the angular domain is divided into sectors, that are accessed via beamforming on a time division basis, to detect signals from primary users. We study the performance of detection metrics based on energy received per beam, and also eigenvalue-based detection statistics through considering the covariance matrix across the various directional beams. The ESPAR is able to achieve over 6dBi SNR improvement due to its beamforming capability. Further, once primary users' signals have been detected, directional transmit opportunities which do not interfere with active PUs become available, and we develop an adaptive beamforming algorithm to capitalise on these to efficiently utilise the spatial domain, which numerically optimises the beampattern and antenna efficiency using a convex formulation. The resulting beampatterns give between -20dB and -30dB nulls in the primary user direction.

Managing uncoordinated interference becomes a substantial problem for heterogeneous networks, since the unplanned interferences from the femtos cannot be coordinately aligned with that from the macro/pico base stations (BSs). Due to the uncoordinated interference, perfect interference alignment (IA) may be not attained. In order to achieve linear capacity scaling by IA, we follow the rank-constrained rank minimization (RCRM) framework which minimizes the rank of the interference subspace with full rank constraint on the direct signal space. Considering that the sum of log function can obtain low-rank solutions to linear matrix inequality (LMI) problems for positive semidefinite matrices, we introduce sum of log function as an approximation surrogate of the rank function. To minimize the concave function, we implement a Majorization-Minimization (MM) algorithm and develop a reweighted nuclear norm minimization algorithm with a weight matrix introduced. Moreover, considering the practical available signal-to-noise ratio (SNR), a mixed approach is developed to further improve the achievable sum rate in low-to-moderate SNR region. Simulation results show that the proposed algorithm considerably improves the sum rate performance and achieves the highest multiplexing gain than the recently developed IA approaches for various interference channels.

We propose a low-complexity vector perturbation (VP) precoding scheme for the downlink of multi-user multiple input multiple output (MU-MIMO) systems. While conventional VP performs a computationally intensive sphere search through multiple candidate perturbation vectors to minimize the norm of the precoded signal, the proposed precoder applies a threshold to the desired norm to reduce the number of search nodes visited by the sphere encoder. This threshold is determined by the performance requirements of the mobile users. Once the threshold is met, the search for the perturbation vectors finishes thus saving significant computational burden at the transmitter. To evaluate the advantages of the proposed technique compared to VP, we further derive the computational complexity in terms of the volume of the associated search space and the resulting numerical operations. In addition, we use a new performance-complexity metric to study the relevant tradeoff and look at the power efficiency of the system, both of which metrics can be used to optimize the user-determined threshold accordingly\color{black}. The presented analysis and results show that the proposed thresholded VP (TVP) offers a favorable tradeoff between performance and complexity where significant complexity reduction is attained while the user threshold performance is guaranteed.

We explore the performance of multiple input multiple output (MIMO) transmitters in correlated channels where increasing numbers of antenna elements are fitted in a fixed physical space. As well investigated in the literature, two main effects emerge in such a design: transmit spatial correlation and mutual antenna coupling. In contrast to the literature however, here we investigate the combined effect of reducing the distance between the antenna elements with increasing the number of elements in a fixed transmitter space. In other words, towards the implementation of large-scale MIMO transmitters in limited physical spaces, we investigate the joint effect of two contradicting phenomena: the reduction of spatial diversity due to reducing the separation between antennas and the increase in transmit diversity by increasing the number of elements. Within this context, we analytically approximate the performance of two distinct linear precoding designs. The theoretical analysis and simulations show the somewhat surprising result that for a given number of receivers the improved transmit diversity dominates the performance of practical linear precoders. Consequently, important benefits in the system sum rate can be gleaned by fitting more antenna elements in a fixed space by employing separations smaller than the wavelength of the transmit frequency.

This paper investigates the multiuser diversity introduced by opportunistic user selection in cognitive radio (CR) networks, where multiple cognitive users request to access the spectral resources of the licensed (primary) user. We investigate a simple cognitive user selection strategy aiming at maximizing the received signal-to-interference-plus-noise ratio (SINR) for a given power budget, under interference constraints to the primary. We study the statistics of the SINR at the cognitive receiver, and derive exact analytical expressions of its probability density function (PDF). We then analytically calculate the diversity gains introduced in the system due to the selection of one cognitive user amongst multiple candidates compared to the case when only one cognitive user exists and no selection occurs. Furthermore, we utilize the PDF of the SINR to predict the bit error rate (BER) of the selected cognitive user. Finally, the asymptotic behavior of the diversity gains for the low transmit power region of the primary and cognitive links, and as the number of candidate links becomes large is also investigated. All three multiaccess scenarios are investigated, namely multiple access channel (MAC), broadcast channel (BC) and parallel access channel (PAC), and the results show that the analytically derived expressions closely match simulated performance.

This paper considers the spectrum sharing multiple-input multiple-output (MIMO) cognitive radio network, in which single primary user (PU) coexists with multiple secondary users (SUs). Joint beamforming and admission control with adaptive modulation technique is designed to maximize the number of the serviced SUs and the transmit rate of the secondary links while imposing upper limits on the interference temperature to the PU by using the least transmit power. In the proposed cross-layer design, the SINR target is dynamically adapted with channel condition and bit-error rate (BER) requirement, and works as admission control implicitly, that is, the cognitive link is dropped as long as its SINR requirement is equal to zero. With the pre-fixed receiver, the multi-objective optimization problem is NP-hard, which is further transformed into single problem by introducing a utility function. The optimum solutions are achieved via second-order cone programming (SOCP) with an iterative bisection search method. Simulation results show that the proposed scheme achieves desirable spectrum and power efficiency, and the maximum number of the total active SUs are intelligently selected.

In this paper, we investigate the outage performance of interference aided adaptive linear precoding in the downlink of a multiuser multiple-input-single-output (MISO) overlay cognitive radio (CR) network. While previous research studies on linear precoding techniques in CR network aim to limit or completely cancel the interference to the primary users while achieving maximum downlink throughput of the CR system, we here make use of adaptive linear precoding at the cognitive base station (CBS) to exploit the interference to the primary and the secondary systems. We show by analysis and simulations that the outage performance of the proposed precoding technique is significantly enhanced in comparison to the conventional techniques.

This paper presents a detailed sum rate characterization of distributed multiple-input multiple-output systems operating over composite fading channels and employing linear zero-forcing receivers. We consider the Rayleigh/Lognormal fading model and also take into account the effects of path-loss and spatial correlation at the transmit side. New closed-form upper and lower bounds on the achievable sum rate are proposed that apply for arbitrary numbers of antennas. Moreover, we investigate the concept of large-scale multiple-antenna systems when the number of receive antennas grow large. In this asymptotic regime, it is shown that the effects of Rayleigh fading are averaged out and the channel is dominated by the much more slowly varying shadowing. An interesting observation from our results is that in order to maximize capacity, the radio ports should be placed at unequal distances to the base station when they experience the same level of shadowing.

This paper is concerned with the study of secrecy capacity for the log-normal fading channel in which the main channel is correlated with the eavesdropper channel. Perfect secrecy is achieved when the transmitter and legitimate receiver can communicate at some positive rate, while insuring that the eavesdropper gets zero bits of information. We consider the full channel state information (CSI) case, where the transmitter has access to both the main channel and eavesdropper channel gains. Under this assumption, we define the secrecy capacity of single-input single-output (SISO) log-normal fading channel and find the optimal power allocation at the transmitter that achieves the secrecy capacity. By analyzing the resulting secrecy capacity, we quantify the loss of secrecy capacity due to the correlation. We also find the closed-form analytical expression for the upper bound of secrecy capacity in terms of correlation coefficient which includes the independent case as a special one. The analysis of upper bound tells how the correlation coefficient and the ratio of main and eavesdropper channel gains affect the secrecy capacity.

Along with the channel capacity, the error exponent is one of the most important information theoretic measures of reliability, as it sets ultimate bounds on the performance of communication systems employing codes of finite complexity. In this paper, we derive the closed-form expressions of Gallager's random coding and expurgated error exponents for Nakagami-m fading keyhole multiple-input multiple-output (MIMO) channels under the assumption that there is no channel-state information (CSI) at the transmitter and perfect CSI at the receiver. From the derived analytical expressions, we get insight into an elementary tradeoff between the communication reliability and information rate of the Nakagami-m fading keyhole MIMO channels. Moreover, we can easily compute the necessary codeword length without the extensive Monte-carlo simulation to achieve predefined error probability at a given rate below the channel capacity. In addition, we derive the exact closed-form expressions for the cutoff rate, critical rate and expurgation rate based on easily computable Meijer G-function. Numerical results are presented and verified via Monte Carlo simulation.

In this paper, an improved multiple input multiple output Tomlinson-Harashima precoder (MIMO-THP) is introduced, where the transmit power loss is reduced based on optimizing the interference to be canceled. The concept behind the proposed technique builds on the fact that both the desired and interfering signals originate from the base station (BS) of the downlink system itself. Based on this observation, the proposed method influences the resulting interference, to reduce the transmission power required to cancel it, without altering the information content of the downlink message. The aim is to bring the interference closer to the replicas of the desired symbols for all users in the THP modulo-extended constellation. In this way, the power required to pre-subtract interference is decreased. Theoretical and simulation results both confirm that, by optimizing the interference to be canceled, the proposed technique offers a considerable transmit power reduction compared to conventional THP while securing an equal error rate performance.

Along with the channel capacity, the error exponent is one of the most important information theoretic measures of reliability, as it sets ultimate bounds on the performance of communication systems employing codes of finite complexity. In this paper, we derive the closed-form expressions for the Gallager's random coding and expurgated error exponents for Rayleigh fading product multiple-input multiple-output (MIMO) channels under the assumption that there is no channel-state information (CSI) at the transmitter and perfect CSI at the receiver. From the derived analytical expressions, we get insight into an elementary tradeoff between the communication reliability and information rate for the Rayleigh fading product MIMO channels. Moreover, we can easily compute the necessary codeword length without the extensive Monte-carlo simulation to achieve predefined error probability at a given rate below the channel capacity. In addition, we derive the exact closed-form expressions for the ergodic capacity and cutoff rate based on easily computable Meijer G-function. The closed-form expressions for the error exponents, ergodic capacity and cutoff rate have also been derived for Rayleigh fading keyhole MIMO channels as the example of special case.

We consider the problem of secret communication through cognitive relay assisted interference channels where the secondary users are allowed to transmit simultaneously with the primary users over the same channel in the presence of an eavesdropper. At first, we investigate the effect of diversity in enhancing security of the cognitive interference channels with multiple relays. Then, the performance of cognitive relay beamforming system is optimized in such a way that the eavesdropper gets zero bits of information maintaining interferences at the primary receiver under a certain threshold. Finally, we characterize secrecy rate at the primary and secondary receivers compensating interferences using zero-forcing (ZF) precoding at the cognitive relay.

The essential tradeoff between sensing capability and achievable throughput of the secondary network is one of the active research topics for researchers working on cognitive radio. In this paper, noise uncertainty which has a great impact on sensing methods is taken into account in the maximization of throughput using eigenvalue based spectrum sensing schemes. This issue has not been tackled in the throughput associated studies before. First, the theoretical and empirical distributions of the decision statistics and the detection performances for eigenvalue based sensing techniques are studied in the presence of noise uncertainty. The computed detection probabilities of maximum-minimum eigenvalue (MME) detector and maximum eigenvalue detector (MED) are compared with the most widely used energy detector (ED). Then, in the light of the obtained results, the throughput of the secondary network is maximized in order to find out the sensing duration for each scheme using multiple receive antennas. It is shown that, under low signal to noise ratio (SNR) regime, the designed sensing slot duration achieves the best sensing throughput tradeoff.

We investigate the outage performance of relay assisted transmissions of coexisting radio systems. Employing simple linear precoding designs, we explore the potential of utilising the cross-interference between the two coexisting systems to mutually improve performance. While conventionally the aim of the relay is to isolate the two concurrent transmissions by completely removing the interference between them, we make use of interference energy when the interference between the two systems is mutually constructive. In this direction two adaptive linear precoding techniques are proposed for the relay and compared to conventional precoding. We use the cognitive radio paradigm to illustrate the associated benefits. It is shown by theoretical analysis and simulation that the constructive interference provides a source of additional green signal energy that benefits the outage performance of both communication links.

In this work, a robust joint signal and interference alignment is designed for cognitive multiple-input multiple-output (MIMO) interference channel in which single primary link coexists with multiple secondary links. Considering channel imperfections and finite signal-to-noise ratio (SNR) in practice, we propose a worst-case joint design to not only minimize the leakage of interference signals but also ensure the desired signal falling into the orthogonal complement of interference subspace. Under the assumption of the norm-bounded channel uncertainties, the underlying problem is recast to convex form via semidefinite programming (SDP), and the optimum solutions are obtained iteratively. Simulation results reveal the effectiveness of the proposed joint design, and robustness of the worst-case design against channel uncertainties.

This paper is concerned with the study of confidential communication through independent and identically distributed (i.i.d.) and evenly correlated Rayleigh fading channels, where a single antenna transmitter communicates with the corresponding receiver in the presence of an eavesdropper. Both the receiver and eavesdropper are equipped with multiple antennas and employ diversity combining receptions such as maximal ratio combining (MRC) and selection combining (SC) diversities. In the presence of channel diversity, we derive the upper and lower bounds on the secrecy capacity with full channel state information (CSI) at the transmitter. The closed-form expression for the upper bound is also derived at high signal-to-noise ratio (SNR) regime. The analysis of upper bound with the diversity combining techniques tells how the channel diversity enhances secrecy capacity. Moreover, as a result of deriving the expression in a closed-form, it is insightful to see, how the channel parameters such as correlation coefficient and the ratio of main and eavesdropper channel gains that will be called average channel gain ratio (CGR) affect the secrecy capacity.

In this paper, we study the error exponent of generalized-K fading multiple-input multiple-output (MIMO) channels over Orthogonal Space-Time Block Codes (OSTBC). Error exponent sets ultimate bounds on the performance of communication systems employing codes of finite complexity and has been seen as one of the most significant information theoretic measures of reliability. In this paper, closed-form expressions of Gallager's random coding and expurgated error exponents for generalized-K fading MIMO channels over OSTBC are derived, assuming that there is no channel-state information (CSI) at the transmitter and perfect CSI at the receiver. Based on which, we gain valuable insight into the fundamental tradeoff between the communication reliability and information rate of the channel. The necessary codeword length to achieve predefined error probability at a given rate below the capacity of channel is identified. Moreover, we derive closed-form expressions for the cutoff rate, critical rate and expurgation rate.

This work focuses on the admission of new (secondary) users in a network where existing (primary) users are interference aligned. One of the challenges in this scenario is to achieve the promised degrees of freedom for the secondary users with limited available dimensions. We design a secondary admission network to achieve interference alignment as in equivalent general peer-peer networks, even when the secondary nodes are configured with limited antenna/spatial dimensions, along with a very strict zero-interference constraint from the primary network. To provide enough dimensions for secondary users to achieve interference alignment, we utilize three effective methods: a) time extension structure; b) adaptivity to network partial connectivity; c) partial interference alignment. The presented analysis shows how the degrees of freedom (DoF) can be achieved for the secondary network in both the constant and time-variant channels.

In this study, the authors derive the effective capacity limits for multiple antenna channels which quantify the maximum achievable rate with consideration of link-layer delay-bound violation probability. Both correlated multiple-input single-output and multiple-input multiple-output keyhole channels are studied. Based on the closed-form exact expressions for the effective capacity of both channels, the authors look into the asymptotic high and low signal-to-noise ratio regimes, and derive simple expressions to gain more insights. The impact of spatial correlation on effective capacity is also characterised with the aid of a majorisation theory result. It is revealed that antenna correlation reduces the effective capacity of the channels and a stringent quality-of-service requirement causes a severe reduction in the effective capacity but can be alleviated by increasing the number of antennas.

This paper investigates the performance of optimal single stream beamforming schemes in multiple-input multiple-output (MIMO) dual-hop amplify-and-forward (AF) systems. Assuming channel state information is not available at the source and relay, the optimal transmit and receive beamforming vectors are computed at the destination, and the transmit beamforming vector is sent to the transmitter via a dedicated feedback link. Then, a set of new closed-form expressions for the statistical properties of the maximum eigenvalue of the resultant channel is derived, i.e., the cumulative density function (cdf), probability density function (pdf) and general moments, as well as the first order asymptotic expansion and asymptotic large dimension approximations. These analytical expressions are then applied to study three important performance metrics of the system, i.e., outage probability, average symbol error rate and ergodic capacity. In addition, more detailed treatments are provided for some important special cases, e.g., when the number of antennas at one of the nodes is one or large, simple and insightful expressions for the key parameters such as diversity order and array gain of the system are derived. With the analytical results, the joint impact of source, relay and destination antenna numbers on the system performance is addressed, and the performance of optimal beamforming schemes and orthogonal space-time block-coding (OSTBC) schemes are compared. Results reveal that the number of antennas at the relay has a great impact on how the numbers of antennas at the source and destination contribute to the system performance, and optimal beamforming not only achieves the same maximum diversity order as OSTBC, but also provides significant power gains over OSTBC.

This paper investigates the potential of exploiting interference as a source of green signal energy in parallel transmissions of co-existing radio systems assisted by a cognitive relay. Assuming a cognitive radio setup, the purpose of the relay is to allow the resources of a primary downlink to be efficiently utilised by a secondary system. While conventionally the relay aims to completely remove the interference, we investigate a strategy of making use of interference energy when the cross-interference between the two systems is mutually constructive. In this way, the interference that already exists in the communication medium provides a source of green signal energy that mutually enhances the received signal power of primary and secondary users without the need to raise the transmitted power. In this direction two adaptive linear precoding techniques are proposed for the cognitive relay and compared to conventional precoding. The effect of green interference on the received signal to noise ratio (SNR) of the primary and secondary users is studied through theoretical analysis and used to predict the resulting error probability and outage performance. The results show that by exploiting free interference power, the secondary downlink can access the primary resources without deteriorating the primary users' performance.

This letter presents an analytical performance investigation on the cognitive broadcast channels (BC) with user selection. Exact closed-form expressions for the outage probability and multiuser interference diversity gain of the cognitive BC are derived. In addition, closed-form upper and lower bounds for the ergodic capacity of the system are presented. These analytical results not only provide fast and efficient means to evaluate the performance of the system, they also enable us to gain valuable insights on the impact of key parameters such as peak transmit power, interference temperature constraint, primary transmit power and channel fading parameters on the system performance.

This paper investigates the multiuser diversity introduced by opportunistic user selection in the cognitive radio parallel access channel (CR-PAC), where multiple cognitive users request to access the spectral resources of the licensed user. Assuming a simple cognitive user selection strategy based on maximizing the received signal-to-interference-plus- noise ratio (SINR), we study the statistics of the SINR at the cognitive receiver. We then use this to analytically calculate the diversity gains introduced in the system due to the selection of one cognitive user amongst multiple candidates, compared to the case when only one cognitive user exists in the network and no selection occurs. Finally, we investigate potential gains for the primary network from this user selection. The results show a close match between analytical expressions and simulation results, while a tight lower bound for the multiuser gain is derived in closed form.

In this paper, we introduce two novel upper bounds on the achievable sum rate of multiple-input multiple-output (MIMO) systems with Zero-Forcing (ZF) receivers. The presented bounds are given in tractable closed-form and apply for different fading models, like uncorrelated/doubly correlated Rayleigh fading and Ricean fading. In addition, the first bound establishes an interesting relationship between the sum rate and the first negative moment of the unordered eigenvalue of the instantaneous correlation matrix. Based on our analytical expressions, we are able to explore the impact of the model parameters, such as number of antennas, spatial correlation and Ricean-K factor, on the sum rate of MIMO ZF receivers.

In this paper, we study the eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. First, we study the extreme eigenvalue distributions of a complex Wishart matrix and then, in contrast to the asymptotic analysis reported in the literature, we derive the exact distribution of the test statistics of (i) maximum eigenvalue detector (MED) (ii) maximum-minimum eigenvalue (MME) detector and (iii) energy with minimum eigenvalue (EME) detector for finite number of samples (n) and finite number of antennas (m). These distributions are represented by complex hypergeometric functions of matrix argument, which can be expressed in terms of complex zonal polynomials. We also describe the method to compute these complex hypergeometric functions. Based on these exact distribution of the test statistics we find the exact decision thresholds as a function of the desired probability of false-alarms for MED, MME and EME. Simulation results show superior performance compared to the decision thresholds obtained from asymptotic (i.e, n,m → ∞) distributions.

In this paper, we consider the problem of secret communication through Rayleigh fading single-input multiple-output (SIMO) broadcast channel in the presence of an eavesdropper. At first, we define the ergodic secrecy capacity and find the optimal power allocation at the transmitter that achieves the secrecy capacity for the full channel state information (CSI) case, where transmitter has access to both the main channel and eavesdropper's channel gains, and for the case of only main channel CSI at the transmitter. Then, we define the secrecy capacity in case of open-loop transmission scheme and present the analytical expression for the lower bound of ergodic secrecy capacity. We also find the analytical expression for secure outage probability to study the secure outage performance of the proposed model.

This paper presents an analytical investigation on the performance of optimal beamforming scheme in multiple-input multiple-output dual-hop amplify-and-forward systems. We first derive a set of new closed-form expressions for the statistical properties of the resultant channel matrix, including the cumulative distribution function and probability density function of the maximum eigenvalue, as well as their first order asymptotic expansions. These analytical expressions are then applied to derive some important performance metrics of the system, i.e., outage probability, diversity order, array gain and ergodic capacity. Numerical simulations are carried out to validate the correctness of the analytical results.

In this paper, we investigate the performance of a dual-hop amplify-and-forward relay system in Nakagami-\emph{m} fading channels in the presence of multiple interferers. Based on the new closed-form expression for the cumulative distribution function of a new type of random variable involving a number of independent gamma random variables, we present closed-form expressions for the outage probability, general moments for the end-to-end signal to interference and noise ratio and ergodic capacity of the system. In addition, we look into the high signal to noise ratio regime and characterize the diversity order and coding gain achieved by the system. Our result shows that the diversity of the system is limited by the hop experiencing more severer fading. Moreover, the interference does not reduce the diversity order of the system, instead, it degrades the outage performance by affecting the coding gain of the system.

This paper investigates linear precoding designs for cognitive relay assisted transmissions of coexisting radio systems. The aim of this work is to characterise the interference between the primary and secondary systems in the cognitive radio setup when transmission is assisted by a cognitive relay. While conventionally the aim of the relay is to completely remove the interference between primary and secondary transmissions, we explore the potential of making use of interference energy when the interference between the two systems is mutually constructive. In this direction two adaptive linear precoding techniques are proposed for the cognitive relay and compared to conventional precoding. The presented theoretical analysis and simulations show that the proposed outperform conventional techniques, as the existence of constructive interference energy improves the received signal to noise ratio (SNR) at both primary and secondary receivers.

We consider the problem of secret communication over Nakagami-m fading multiple-input single-output (MISO) broadcast channel, where transmitter sends messages to the destination users following two different transmission protocols. In the first transmission protocol, transmitter sends a confidential message to user 1, and user 2 acts as an eavesdropper. In this protocol, at first, we define the ergodic secrecy capacity for the full channel state information (CSI) case and then we consider the case of only main channel CSI at the transmitter. Finally, we define the secrecy capacity in case of open-loop spatial multiplexing transmission scheme and present the analytical expression for the lower bound of ergodic secrecy capacity. In the second transmission protocol, we consider the transmission of two independent messages to user 1 and user 2 with information-theoretic secrecy, where each user would like to obtain its own confidential message in a reliable and safe manner. Under this communication scenario, an achievable secrecy capacity region is developed using secret dirty-paper coding scheme.

This paper presents an analytical performance investigation of the capacity limits of correlated multiple-input single-output (MISO) channels in the presence of quality-of-service (QoS) requirements. Exact closed-form expression for the effective capacity of correlated MISO channels is derived. In addition, simple expressions are obtained at the asymptotic high and low signal-to-noise ratio (SNR) regimes, which provide insights into the impact of various system parameters on the effective capacity of the system. Also, a complete characterization of the impact of spatial correlation on the effective capacity is provided with the aid of a majorization theory result. The findings suggest that antenna correlation reduce the effective capacity of the channels. Moreover, a stringent QoS requirement causes a significant reduction in the effective capacity but this can be effectively alleviated by increasing the number of antennas.

In this paper, we analyze the asymptotic outage probability performance of both decode-and-forward (DF) and amplify-and-forward (AF) relaying systems using partial relay selection and the best relay selection schemes for Nakagami-m fading channels. We derive their respective outage probability expressions in the asymptotic high signal-to-noise ratio (SNR) regime, from which the diversity order and coding gain are analyzed. In addition, we investigate the impact of power allocation between the source and relay terminals and derive the diversity-multiplexing tradeoff (DMT) for these relay selection systems. The theoretical findings suggest that partial relay selection can improve the diversity of the system and can achieve the same DMT as the best relay selection scheme under certain conditions.

This paper investigates the achievable sum rate of Rayleigh product MIMO channels with linear MMSE receiver. Exact closed-form expressions are derived, which provide an efficient means to evaluate the achievable sum rate of the system with arbitrary number of antennas and scatters. In addition, simple expressions were obtained for the key parameters dictating the sum rate performance of the system at the high and low signal to noise ratio regime, which enables us to gain insights on how system parameters such as the number of scatters affect the achievable sum rate of the system. Our analytical results confirm the intuition that increasing the number of scatters improves the achievable sum rate of the system.

Transmit beamforming is designed for multiple-input multiple-output (MIMO) cognitive radio network in which single primary user (PU) coexists with single secondary user (SU). The proposed cognitive beamforming minimizes the transmit power of the SU while limiting the interference temperature to PU and achieving the signal-to-interference-plus-noise ratio (SINR) target at SU. With perfect knowledge of channel information and receive beamforming pattern of the PU, the optimization problem is formulated as quadratically constrained quadratic programming (QCQP), and the optimal solution is obtained by using semidefinite programming relaxations (SDR). A probabilistic approach is developed by guaranteeing the interference temperature below a pre-specified threshold with high probability for the case when no knowledge of receive beamforming vector of the PU is available at the SU transmitter (SU-Tx). Simulation results demonstrate the effectiveness of the proposed approach in both scenarios.

We consider the overlay cognitive radio channel where the cognitive user is admitted to transmit simultaneously with the primary user provided that the instantaneous rate of primary link is not degraded. Assuming causal knowledge of the primary user's message at the cognitive transmitter (CT), we analyze the transmission rates of the cognitive user in the single-input multiple-output (SIMO) and the multiple-input single-output (MISO) configurations. In particular, the CT uses a part of its transmit power to assist the primary user in delivering the primary user's message and the other part of its power is used to deliver its own message. The transmit power and the beamformers are designed to maximize the rate of the cognitive user while fixing the the rate of the primary user. Our simulation results show that the proposed scheme yields improved system performance compared to the interweave scheme where any interference to the primary user is prohibited.

In this paper, we consider a Rayleigh fading multiple-access interference channel where a group of users communicate with a receiver in the presence of multiple Gaussian interferers. We derive the closed-form analytical expressions for the ergodic sum-capacity in case of uncorrelated multiple-input multiple-output (MIMO) channel and spatially uncorrelated orthogonal space time block coded (OSTBC) MIMO channel. As the example of special cases, we also show the ergodic sum-capacity for the multiple-input single-output (MISO) and single-input single-output (SISO) channels. Moreover, we derive the analytical expression for the complementary cumulative distribution function (CCDF) of sum-capacity in case of OSTBC MIMO channel. Numerical results are presented and verified via Monte-Carlo simulation.

In this paper, we derive the closed-form Gallager's random coding error exponent expression for Orthogonal Space-Time Block Coded (OSTBC) Nakagami-m fading multiple-input multiple-output (MIMO) channels. We assume that the transmitter has no channel-state information (CSI) and perfect CSI at the receiver. We get the knowledge of an elementary tradeoff between the communication reliability and information rate of the OSTBC Nakagami-m fading MIMO channels by this measure. At a given rate below the channel capacity, it enables us to find the necessary codeword length to achieve predefined error probability. We derive the expression for the cutoff rate and ergodic capacity based on easily computable Meijer G-function. Numerical results are presented and verified via Monte-Carlo simulation.

This paper studies the Demmel condition number of Wishart matrices, a quantity which has numerous applications to wireless communications, such as adaptive switching between beamforming and diversity coding, link adaptation, and spectrum sensing. For complex Wishart matrices, we give an exact analytical expression for the probability density function (p.d.f.) of the Demmel condition number, and also derive simplified expressions for the high tail regime. These results indicate that the condition of complex Wishart matrices is dominantly decided by the difference between the matrix dimension and degree of freedom (DoF), i.e., the probability of drawing a highly ill conditioned matrix decreases considerably when the difference between the matrix dimension and DoF increases. We further investigate real Wishart matrices, and derive new expressions for the p.d.f. of the smallest eigenvalue, when the difference between the matrix dimension and DoF is odd. Based on these results, we succeed to obtain an exact p.d.f. expression for the Demmel condition number, and simplified expressions for the high tail regime.

In this paper, we study the statistical distribution of the Demmel condition number of complex Wishart matrices, a quantity which has found numerous applications to wireless communications, such as adaptive switching, link adaptation, and spectrum sensing. We give an exact analytical expression for the probability density function (p.d.f.) of the Demmel condition number, and also derive simplified expressions for the high tail regime. These results indicate that the condition of complex Wishart matrices is dominantly decided by the difference between the matrix dimension and degree of freedom (DoF).

This paper presents a method to significantly reduce the preprocessing complexity of the sphere decoder (SD) in frequency-selective channels. The method consists of calculating an approximate QR decomposition (AQRD) of the channel matrix, making use of its special Toeptliz and block-Topelitz structure in single and multiple-antenna frequency-selective channels, respectively. The AQRD obtains the QR decomposition of a small submatrix of the channel matrix and extends that result to the rest of the matrix, resulting in a considerable complexity reduction compared to the original full QR decomposition (FQRD). Simulation results show that, despite the lower complexity of the AQRD, it causes only a small bit error rate (BER) performance degradation in the SD.

In this paper, we consider the transmission of confidential message through non-identically and identically independent Nakagami-m fading single-input multiple-output (SIMO) channel in the presence of an eavesdropper. We are interested in protecting this message against eavesdropping i.e. the information is secure if it cannot be eavesdropped by any eavesdropper. Based on the problem of secure communications between transmitter and intended receiver over Nakagami-m fading channel where an eavesdropper observes their transmissions through another Nakagami-m fading channel, we derive the analytical expressions for the probability of non-zero secrecy mutual information, secure outage probability and ergodic secrecy mutual information of SIMO wireless communication systems over non-identically and identically independent Nakagami-m fading subchannels. Numerical results are presented and verified via Monte-Carlo simulation.

We consider a single-input multiple-output (SIMO) Rayleigh fading broadcast channel, where the transmitter sends some confidential information to one user which is a legitimate receiver in the presence of multiple eavesdroppers. The eavesdroppers are mutually independent and perfect secrecy is achieved when the transmitter and the legitimate receiver can communicate at some positive rate, while insuring that each eavesdropper gets zero bits of information. Here, we find the probability of non-zero secrecy mutual information and secure outage probability to investigate the outage behavior of proposed model. We also present a formulation of ergodic secrecy mutual information in the presence of multiple eavesdroppers.

In this paper, we consider a cognitive relay assisted multiple-input multiple-output (MIMO) communication scenario through Rayleigh fading channel where multiple primary and secondary users wish to communicate with two different receivers in the presence of a cognitive relay. We assume that secondary users transmit simultaneously with the primary users over the same channel instead of waiting for an idle channel which is traditional for a cognitive radio. We consider both the cases when cognitive relay is present or not and derive the expressions for the mutual information received at the primary and secondary receivers. We also present the closed form expressions for the outage probabilities and complementary cumulative distribution functions (CCDFs) of mutual information received at the primary and secondary receivers in the absence of cognitive relay. Our results show that with the help of a cognitive relay, not only both the primary and secondary users are able to communicate with their intended receivers compensating interferences created at their receivers, but also the outage performance of primary and secondary users are improved due to the additional diversity obtained via cognitive relaying.

In the group-oriented applications such as military and commercial wireless cellular networks often require the same data to be conveyed to multiple users simultaneously. This technique is usually referred to as physical layer multicasting. In this paper, we are interested in protecting these data from eavesdropping. Here, we consider the transmission of confidential data through slow fading channels in the presence of single as well as multiple eavesdroppers. We define the perfect secrecy multicast mutual information in terms of secure outage probability for three different scenarios of secure wireless multicasting and provide a complete characterization of the maximum transmission rate at which the eavesdropper/eavesdroppers is/are unable to decode any information. We also present the average secrecy mutual information for multicasting in the presence of multiple eavesdroppers.

In this paper, we propose exact decision thresholds for “blindly combined energy detection (BCED)” in the case of multiple receiver collaborative spectrum sensing. As opposed to the decisions thresholds estimation based on an asymptotic analysis in the sense of large samples and/or large collaborative antennas presented in the literature, the proposed mathematical formulation can be used to calculate exact thresholds for finite number of samples and collaborative antennas. The proposed formulation is based on our recent progress in the exact eigenvalue distributions of complex Wishart matrices with finite sizes. Moreover, the proposed thresholds valid for both correlated and uncorrelated Gaussian noise cases. Finally, we show that the probability of detection performance with the proposed exact decision thresholds performs better than the performance achieved with the decision thresholds calculated based on the asymptotic analysis, thus validate the importance of this work.

This paper studies the ergodic capacity of multiple-input multiple-output (MIMO) systems with a single co-channel interferer in the low signal-to-noise-ratio (SNR) regime. Two MIMO models namely Rician and Rayleigh-product channels are investigated. Exact analytical expressions for the minimum energy per information bit, Eb/N0min, and wideband slope, S0, are derived for both channels. Our results show that the minimum energy per information bit is the same for both channels while their wideband slopes differ significantly. Further, the impact of the numbers of transmit and receive antennas, the Rician K factor, the channel mean matrix and the interference-to-noise-ratio (INR) on the capacity, is addressed. Results indicate that interference degrades the capacity by increasing the required minimum energy per information bit and reducing the wideband slope. Simulation results validate our analytical results.

This paper presents the field-programmable gate array (FPGA) implementation of a variant of the Lenstra-Lenstra-Lovasz (LLL) lattice reduction (LR) algorithm, known as the Clarkson's Algorithm (CA), and its application to uncoded multiple input-multiple output (MIMO) detection. The CA provides practically the same performance as the LLL algorithm while having a considerably lower complexity, especially for MIMO systems with a large number of transmit and receive antennas. The algorithm has been implemented in real-time using a rapid prototyping methodology, greatly reducing its development time. Implementation results indicate that the variable complexity and the sequential nature of LR algorithms, like the CA, remain their main drawbacks from an implementation point of view.

We consider a cognitive relay assisted multiple-input multiple-output (MIMO) communication scenario where multiple secondary users wish to communicate with the secondary receiver through Rayleigh fading channels in the presence of a primary user. We assume that secondary users transmits simultaneously with the primary user over the same channel instead of waiting for an idle channel which is traditional for a cognitive radio. We derive the expressions for mutual information received at the primary and secondary receivers in both the cases when cognitive relay is present or not. We also present the closed form expressions for the outage probabilities and complementary cumulative distribution functions (CCDFs) of mutual information received at the primary and secondary receivers in the absence of cognitive relay. Our results show that in the presence of cognitive relay, not only both the primary and multiple secondary users are able to communicate with intended receivers compensating interferences created at their receivers, but also the outage performance of primary and secondary users are improved due to the additional diversity obtained via cognitive relaying.

This paper considers multiuser MIMO CDMA systems with high rate space-time linear dispersion codes (LDC) and orthogonal space-time block codes (O-STBC) in time-varying Rayleigh fading MIMO channels. We propose a multi-function process integrating multi-user detection, space-time decoding and symbol demodulation, which can be coupled with soft channel decoding to improve the system performance in an iterative fashion. We show that the space-time coded CDMA systems approach the single-user bound with only two iterations, and full diversity LDCs enable the systems to utilize the time diversity inherent in fast fading channels. The space-time coded CDMA systems are also compared to the MIMO CDMA system based on spatial multiplexing, some recommendations are made on how to design a practical MIMO CDMA system based on the comparative studies.

This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.

In this correspondence, the performance of the network coded amplify-forward cooperative protocol is studied. The use of network coding can suppress the bandwidth resource consumed by relay transmission, and hence increase the spectral efficiency of cooperative diversity. A distributed strategy of relay selection is applied to the cooperative scheme, which can reduce system overhead and also facilitate the development of the explicit expressions of information metrics, such as outage probability and ergodic capacity. Both analytical and numerical results demonstrate that the proposed protocol can achieve large ergodic capacity and full diversity gain simultaneously.

This paper presents a soft-output version of the fixed-complexity sphere decoder (FSD) previously proposed for uncoded multiple input-multiple output (MIMO) detection. Thus, the soft-FSD (SFSD) can be used in turbo-MIMO systems to exchange extrinsic soft-information with the outer decoder. For that purpose, the SFSD generates a list of candidates that approximates that of the list sphere decoder (LSD) while containing information about all the possible bit values, removing the need for clipping. In addition, it overcomes the two problems of the LSD: its variable complexity and the sequential nature of its tree search. Simulation results show that the SFSD can be used to approximate the performance of the LSD while having a considerably lower and fixed complexity, making the algorithm suitable for hardware implementation.

The performance and complexity of two complex lattice reduction (LR) algorithms used in multiple input-multiple output (MIMO) detection are compared in this paper. The Seysen's Algorithm (SA) has been previously proposed as a low-complexity alternative to the real version of the Lenstra-Lenstra-Lovasz (LLL) algorithm while providing a better performance in LR-aided linear detectors. However, this paper shows that the SA has a higher complexity than the complex version of the LLL algorithm, due to its more computationally intensive preprocessing stage and its higher complexity per iteration. In addition, both the SA and the complex LLL algorithm provide practically the same performance when used in LR-aided successive interference cancellation (SIC) detectors.

In this paper, we design and analyse a distributed time-reversal space-time block code (D-TR-STBC) that can achieve significant power gain and optimum diversity order in a relay-assisted transmission for single-carrier frequency-selective channels. The idea behind distributed space-time block coding (D-STBC) is to have the relays cooperate in such a way that the signal at the destination is a space-time code, so as to obtain full diversity. In contrast to the literature, we show that the orthogonality of D-TR-STBC can be preserved at the destination by including the signals received via the direct link (from the source to the destination) at the first half of the signalling interval along with the space-time block coded signal received at the second half of the signalling interval. The pairwise error probability (PEP) derivation shows that the proposed scheme achieves the optimum diversity order. Moreover, the symbol error rate (SER) performance of the proposed scheme and competing scheme using different equalization techniques and signal to noise ratios (SNRs) in the source to relay link shows that the proposed protocol outperforms the other by an SNR margin of 2 – 5dB.

In recent years, due to the low complexity nature of the turbo processing and excellent bit-error-rate (BER) performance, designing turbo-like receivers for frequency-selective MIMO channels has been of great research interest. The performance gain in turbo decoders is due to an extrinsic information transfer (EXIT) process between the detection and the decoding stages as compare to a traditional system that treats these processes in isolation. However, the challenge faced with these iterative receivers is the understanding of their performance and convergence behaviour. In this paper, we study an iterative maximum a posteriori (MAP) receiver for MIMO orthogonal frequency division multiplexing (OFDM) channels and its convergence behaviour. We analyze the performance of the proposed transceiver system with Gray and anti-Gray mapping using EXIT chart and study the effects of various settings of transmit and receive antenna on the turbo cliff in BER performance.

The aim of this paper is to study the impact of channel state information on the design of cooperative transmission protocols. This is motivated by the fact that the performance gain achieved by cooperative diversity comes at the price of the extra bandwidth resource consumption. Several opportunistic relaying strategies are developed to fully utilize the different types of a priori channel information. The information-theoretic measures such as outage probability and diversity-multiplexing tradeoff are developed for the proposed protocols. The analytical and numerical results demonstrate that the use of such a priori information increases the spectral efficiency of cooperative diversity, especially at low signal-to-noise ratio.

In this letter, the performance bound of the IEEE 802.16d channel is examined analytically in order to gain an insight into its theoretical potential. Different design strategies, such as orthogonal frequency division multiplexing (OFDM) and single-carrier frequency-domain equalization (SC-FDE), time-domain decision feedback equalization (DFE), and sphere decoder (SD) techniques are discussed and compared to the theoretical bound.

The aim of this paper is to study the impact of channel state information on the design of cooperative transmission protocols. This is motivated by the fact that the performance gain achieved by cooperative diversity comes at the price of the extra bandwidth resource consumption. Several opportunistic relaying strategies are developed to fully utilize the different types of a priori channel information. The analytical and numerical results demonstrate that the use of such a priori information increases the spectral efficiency of cooperative diversity, especially at low signal-to-noise ratio.

In this paper, the performance of the network coded amplify-forward cooperative protocol is studied. The use of network coding can suppress the bandwidth resource consumed by relay transmission, and hence increase the spectral efficiency of cooperative diversity. A distributed strategy of relay selection is applied to the cooperative scheme, which can reduce system overhead and also facilitate the development of the explicit expressions of information metrics, such as outage probability and ergodic capacity. Both analytical and numerical results demonstrate that the proposed protocol can achieve large ergodic capacity and full diversity gain simultaneously.

A low complexity transmit diversity scheme is derived in this paper in order to overcome the prohibitive complexity imposed by the maximum likelihood detection for the systems with space-time block code (STBC) over frequency selective channels. By taking advantage of multipath propagation and exploiting temporal diversity gain, the proposed turbo equalization algorithm significantly improves the system performance compared to the original Alamouti algorithm as well as the conventional minimum mean square error (MMSE) detection scheme.

Cooperative transmission schemes can offer benefits in terms of diversity and multiplexing gain compared with conventional direct transmission by forming a virtual antenna array. In this paper, a spectrally efficient strategy is proposed for cooperative multiple access channels in a centralized communication environment with N users. With help of superposition coding, the deteriorating effect of cooperative communication on the data rate is effectively suppressed since relaying transmission does not consume extra channel use. By carefully categorizing the outage events, the diversity-multiplexing tradeoff can be obtained, which shows that the proposed strategy can achieve optimal tradeoff for multiplexing gains 0 les r les 1 whereas the compared cooperative scheme is only optimal for 0 les r les 1/N.

In this paper we consider a cooperative communication system where some a priori information of wireless channels is available at the transmitter. Several opportunistic relaying strategies are developed to fully utilize the available channel information. Then an explicit expression of the outage probability is developed for each proposed cooperative scheme as well as the diversity-multiplexing tradeoff by using order statistics. Our analytical results show that the more channel information available at the transmitter, the better performance a cooperative system can achieve. When the exact values of the source-relay channels are available, the performance loss at low SNR can be effectively suppressed. When the source node has the access to the source-relay and relay-destination channels, the full diversity can be achieved by costing only one extra channel used for relaying transmission, and an optimal diversity-multiplexing tradeoff can be achieved d(r) = (N + 1)(1 - 2r), where N is the number of all possible relaying nodes.

A new multistage sphere decoder (MSD) for the detection of multiple input-multiple output (MIMO) systems in frequency- selective channels is presented in this paper. The algorithm is based on the Schnorr-Euchner (SE) version of the sphere decoder (SD) but reduces its complexity by dividing the tree search of the SD in a number of non-overlapping stages that directly determine its performance and complexity. The MSD performs a reduced-size tree search in each one of the stages, applying interference cancellation between them to subtract the effect of previously searched stages. By selecting the number of stages of the MSD, different levels of performance can be attained, ranging from the maximum likelihood (ML) performance of the SD and the performance of the generalized decision feedback equalizer (GDFE). Simulations show that the MSD can reduce the complexity of the SD while approaching its ML performance. In particular, by reducing the worst-case complexity of the SD, the MSD is more suitable for hardware implementation even though it still presents a variable complexity.

We design and analyze spectrally efficient half-duplex cooperative diversity protocols using multiple relays (say JV), which combat the multi-path fading by retransmitting the bit-interleaved coded information transmitted by a source to destination. In the first proposed protocol, the relay with the best mutual information relay path (source-relay-destination) will relay the source information - thus termed as best-relay protocol. In the second proposed protocol, called N-relay cyclic protocol, each relay will transmit only a portion of the signal transmitted by the source. We derive the probability density functions of the mutual information for both of these protocols and using these densities, we analyze the outage probability and outage capacity performances. The results show that the proposed protocols achieve the maximum diversity order N + 1. The simulation results using turbo code are given and results show the superior performance of the best-relay protocol.

We design and analyze spectrally efficient half-duplex cooperative diversity protocols using multiple relays (say JV), which combat the multi-path fading by retransmitting the bit-interleaved coded information transmitted by a source to destination. In the first proposed protocol, the relay with the best mutual information relay path (source-relay-destination) will relay the source information - thus termed as best-relay protocol. In the second proposed protocol, called N-relay cyclic protocol, each relay will transmit only a portion of the signal transmitted by the source. We derive the probability density functions of the mutual information for both of these protocols and using these densities, we analyze the outage probability and outage capacity performances. The results show that the proposed protocols achieve the maximum diversity order N + 1. The simulation results using turbo code are given and results show the superior performance of the best-relay protocol.

The application of turbo principle in designing receivers for multiple-input multiple-output (MIMO) wireless systems not only achieves practical complexity receiver systems but also near optimal performances for many of the next generation systems. In particular, our recent research has shown that significant performance can be achieved by using a low complexity iterative soft interference cancellation minimum mean-squared error (SIC-MMSE) equalizer in various coded MIMO wireless channels including frequency-selective MIMO channels (S. Ahmed et al., 2006). This performance gain is due to an extrinsic information exchange process between the equalization and the channel decoding stages compared to a traditional system that treats these processes in isolation. However, the challenge faced with these iterative receivers is the understanding of their convergence behaviour. In this paper, to better understand the convergence behaviour of the proposed iterative receiver, we study the notion of extrinsic information transfer (EXIT) characteristics. Using simulations, we derive the extrinsic information trajectory on the EXIT chart at various Eb/N0ranges to confirm the convergence of the proposed equalizer.

We investigate the performance of multirate layered space-time coded MIMO systems with successive decoding and interference cancellation (SDIC) receivers in quasi-static Rayleigh fading channels. The proposed framework can be viewed as a class of diagonal layered space-time coded system with each of the layers is encoded independently with different rates subject to equal per-layer outage probabilities. We derive the probability density functions of the per-layer mutual informations, which can be used to estimate the per-layer rates. Using these densities we show that the proposed transceiver increases the outage capacity. We also present simulation results illustrating the outage capacity performance for a variety of transmit and receive antenna combinations and the associated near optimal per-layer rates of input signals. In particular we show that for sufficiently large numbers of transmit and receive antennas, the system can achieve near capacity in quasi-static fading environments. Based on these results, multirate codes are designed using punctured turbo codes and simulation results show significant gains in packet error-rate (PER) performances compared to that of V-BLAST architectures with lower receiver complexities.

In this paper we focus on the spatial equalizer design for MIMO systems with Rayleigh fading channels where channel information is not available at the receiver. Training based algorithms have been widely used for such communications scenarios due to its performance superiority compared to blind methods. We investigate how to further improve the performance of the training algorithms by incorporating the statistical information from the unknown sequence. By constructing an ICA-based semi-blind criterion, a steepest decent method is applied to find the desired solution adaptively. To further improve the performance and convergence speed of the proposed method, we propose a technique to find the optimal choice of step size. Furthermore a constrained CRB is developed for the addressed semi-blind signal model to evaluate the performance of the proposed algorithm. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes

In this paper, we propose a practical iterative transceiver design for multiple-input multiple-output (MIMO) frequency-selective wireless channels, which is able to realize a significant portion of the capacity promised by information theory. At the transmitter end, we exploit the idea of space-time bit-interleaved coded modulation (ST-BICM) scheme by using turbo or convolutional codes. This encoding scheme is highly effective if used in conjunction with receiver employing iterative detection and decoding. At the receiver end, we propose a novel multi-antenna detection scheme, which equalizes the intersymbol interferences (ISI) and soft estimate the transmitted symbols. These symbols are then input to a sub-optimal turbo-like receiver that performs iterative decoding of the ST-BICM codes in an iterative and, most important, simple fashion. The simulation results show that the proposed so called turbo-MIMO transceiver error performance improves with the number of iterations of the decoding algorithm. This performance improvement will enhance the capacity and quality of the wireless link

An efficient cooperative transmission scheme has been recently proposed based on superposition modulation. Analytical results are necessary to fully understand the superiority of this new scheme, which is the main contribution of this paper. Tight upper and lower bounds of the outage probability of this scheme are first proposed and then the large SNR behavior of the outage probability is studied. Our analytical results prove that the superposition cooperative transmission scheme can achieve around 3 dB better performance and larger diversity order than the selection relaying scenario, which are consistent with the simulation results reported earlier. Finally, we provide outage, delay-limited and ergodic capacity results of cooperative techniques

We study a multirate layered architecture for multiple-input multiple-output (MIMO) quasi-static Rayleigh fading channels, which uses a diagonal space-time interleaved (DSTI) coded modulation and a low complexity linear successive decoding receiver. The key challenge involved with this architecture is estimating the per-layer rates. We derive the probability density functions of per-layer mutual information, which are used to estimate the per-layer rates that maximize the information rate subject to an upper bound on the outage probability. Based on these rates, we design punctured turbo codes and the simulation results show significant gains in bit error rate (BER) performances. In comparison with the BLAST architecture, the proposed multirate system has more practical virtues while achieving near capacity performance for sufficiently large diversity orders

We propose a multirate diagonal space-time interleaved (DSTI) coded modulation system with a low complexity linear successive decoding and interference cancellation receiver for quasi-static Rayleigh fading multiple-input multiple-output (MIMO) channels. In comparison with the traditional BLAST architecture, the proposed multirate DSTI system has more practical virtues while achieving near capacity performance for sufficiently large multiple antennas. The key findings of this paper are: (i) the derivation of the probability density functions of per-layer mutual informations, which can be used to estimate per-layer rates, and (ii) the design of multirate DSTI system using punctured turbo codes. Simulation results show significant gains in packet error-rate (PER) performances.

Two adaptive algorithms (time varying and exponentially weighted) based on the H/sup /spl infin// principles are proposed for the minimization of electrooculogram (EOG) artifacts from corrupted electroencephalographic signals. Performance of the proposed algorithms are compared with the least-mean-square (LMS) algorithm. Improvements in the output signal-to-noise ratio along with time plots are used for the comparison. It is found that the H/sup /spl infin//-based algorithms effectively minimize the EOG artifacts and always outperform the LMS algorithm.

In this correspondence, the densities of quadratic forms on complex random matrices and their joint eigenvalue densities are derived for applications to information theory. These densities are represented by complex hypergeometric functions of matrix arguments, which can be expressed in terms of complex zonal polynomials. The derived densities are used to evaluate the two most important information-theoretic measures, the so-called ergodic channel capacity and capacity versus outage of multiple-input multiple-output (MIMO) spatially correlated Rayleigh-distributed wireless communication channels. We also derive the probability density function of the mutual information between transmitted and received complex signals of MIMO systems with a finite number of transmit and receive antennas. Numerical results show how channel correlation degrades the capacity of MIMO communication systems.

Quadratic forms on complex random matrices and their joint eigenvalue densities are derived with the goal of studying the ergodic channel capacity of multiple-input multiple-output (MIMO) Rayleigh distributed wireless communication channels. We consider MIMO channels which are correlated at the transmitter and/or the receiver ends and evaluate the corresponding ergodic capacity formulas. These formulas are expressed in terms of complex zonal polynomials. This study shows how channel correlation degrades the capacity of the communication systems.

In this paper, a novel H/spl infin/ approach is proposed for tracking of polarized co-channel sources using an array of tripole antennas. The proposed approach partitions the observation data matrix into two sub-matrices that are used, in conjunction with a new state-space model, to provide an H/spl infin/-type recursive estimation of a linear combiner. The linear combiner then provides estimates of the noise and signal subspaces, from which the directions of the incident signals can be estimated and tracked. The proposed technique is also capable of handling the tracking of appearing/disappearing sources during the observation interval and, furthermore, can accommodate array modeling uncertainties. The difficult problem of tracking the crossing sources can be successfully handled by using diversely polarized array.

In this letter, a novel robust technique is proposed to mitigate the degrading effects of finite sampling and imprecise modeling on the performance of the multiple signal classification (MUSIC) algorithm, Initially, a new array-signal state space model is developed, which is valid for any array geometry. Based on this model, formulated in an H/sup /spl infin// framework, a new robust direction-finding approach has been proposed. This theoretical framework is supported by simulation examples that demonstrate the robustness of the new technique to the presence of array uncertainties and signal correlation.

The idea of applying H/sup /spl infin// estimation techniques to the "array uncertainties problem" is motivated by the fact that H/sup /spl infin// estimation is robust to model uncertainties and lack of statistical information with respect to noise. A new state space model for the received signal of a general array of sensors is developed which, in contrast to existing models, is capable of handling the simultaneous presence of different type of uncertainties (e.g., gain, phase, locations, mutual coupling, etc. uncertainties). Based on this state space model, formulated in an H/sup /spl infin// framework, two new robust array signal processing techniques have been proposed which mitigate the degrading effects of array uncertainties.