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This paper presents a multiple-input–multiple-output (MIMO) precoder with a compensated QR decomposition (CQRD) combination for coordinated multipoint (CoMP) downlink transmission. Unlike conventional QR decomposition (QRD) combination, CQRD combination adopts compensated channel matrix orderings. This paper first proposes CQRD combination for CoMP scenarios. The statistics for combined spatial subchannel gains with a CQRD combination of two coordinated base stations (BSs) are derived, and these statistics show that more balanced subchannel gains are generated with a CQRD combination than with a QRD combination. Furthermore, this paper proposes a generalized CQRD combination scheme with a joint sorting strategy that can be applied to scenarios with more than two coordinated BSs. Unlike the unsorted strategy, the joint sorting strategy determines an enhanced compensated combination to further increase spatial subchannel gains; therefore, the performance can be upgraded. Because conventional Tomlinson–Harashima precoding (THP) cannot be used in the CQRD combination, interference presubtraction and vector precoding (VP) is adopted. Theoretical analysis and simulation results are both provided to demonstrate the advantages of balanced spatial subchannel gains and enhanced bit-error-rate (BER) performance in the proposed CQRD-based schemes. Compared with existing QRD-based MIMO precoders in CoMP scenarios, the proposed CQRD-based schemes have substantial signal-to-noise ratio (SNR) improvements of 2–5 dB. [ABSTRACT FROM PUBLISHER]

In this paper, we design receivers for filter bank multicarrier-based (FBMC-based) massive MIMO considering practical aspects such as channel estimation and equalization. In particular, we propose a spectrally efficient pilot structure and a channel estimation technique in the uplink to jointly estimate all the users’ channel impulse responses. We mathematically analyze our proposed channel estimator and find the statistics of the channel estimation errors. These statistics are incorporated into our proposed equalizers to deal with the imperfect channel state information (CSI) effect. We revisit the channel equalization problem for FBMC-based massive MIMO, address the shortcomings of the existing equalizers in the literature, and make them more applicable to practical scenarios. The proposed receiver in this paper consists of two stages. In the first stage, a linear combining of the received signals at the base station (BS) antennas provides a coarse channel equalization and removes any multiuser interference. In the second stage, a per subcarrier fractionally spaced equalizer (FSE) takes care of any residual distortion of the channel for the user of interest. We propose an FSE design based on the equivalent channel at the linear combiner output. This enables the applicability of our proposed technique to small and/or distributed antenna setups such as cell-free massive MIMO. Finally, the efficacy of the proposed techniques is corroborated through numerical analysis. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is a precoding technique that aligns interfering signals at receivers. It is known that IA achieves the maximum degrees of freedom over an interference channel under ideal assumptions. The real-world performance of IA depends on a range of practical issues, such as imperfect synchronization, channel estimation, and feedback. Practical issues have been studied in simulations and prototypes, but fully distributed operation of IA network nodes has not been considered. In this paper, we present the first investigation of real-time IA performance on a fully distributed 2 $\times$ 2 multiple-input–multiple-output (MIMO) prototype system with three physically independent user pairs. Over-the-air algorithms for time and frequency synchronization, as well as analog feedback, are studied and implemented. Sum rates are illustrated as a function of complexity and accuracy of different alignment, synchronization, and feedback algorithms. Corresponding tradeoffs are evaluated using an iterative IA method, the injection of residual frequency offset into synchronization, and analog versus quantization-based limited feedback approaches. We demonstrate that, while considering all possible error sources in estimation, synchronization, and feedback, the theoretical multiplexing gain of IA can be reached in practical systems with a constant sum rate loss that remains within 5 bits/Hz/s compared with an ideal simulation. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an ergodic interference alignment (IA) method for interference elimination in spectrum sharing multiple-input multiple-output (MIMO) radar and multi-user MIMO communication systems. In existing ergodic IA methods, the channel state information (CSI) is generally assumed to be constant, but time-varying channels should be considered in practice. Differently, our proposed ergodic IA allows to time-varying and/or frequency selective channels for spectrum sharing radar-communication systems. The essence is equivalent to design a simple transmit beamforming, which helps to find a pair of desired complementary channels easily without long-time system delay, therefore, the interferences can be effectively cancelled. The proposed method is evaluated by generalized likelihood ratio test (GLRT) and signal to interference plus noise ratio (SINR) for the radar functionality, while the communication functionality is examined by bit error rate (BER) performance. Both theoretical analysis and simulation results validate that the effectiveness of the ergodic IA method for spectrum sharing radar-communication systems. [ABSTRACT FROM AUTHOR]

In multi-user multiple-input–multiple-output (MU-MIMO) systems that employ pilot-symbol aided channel estimation, the pilot-to-data power ratio (PDPR) has a large impact on the system performance. In this paper, we consider the problem of setting the PDPR in multi-cell MU-MIMO systems in the presence of channel estimation errors, intercell interference and pilot contamination. To analyze and address this problem, we first develop a model of the multi-cell MU-MIMO system and derive a closed-form expression for the mean squared error of the uplink received data symbols. Building on this result, we then propose two decentralized PDPR-setting algorithms based on game theoretic approaches that are applicable in multi-cell systems. We find that both algorithms converge to a Nash equilibrium and provide performance improvements over systems that do not properly set the PDPR, while they maintain different levels of fairness. [ABSTRACT FROM AUTHOR]

The main focus of this paper is on multistream multiantenna (multiple-input multiple-output) communications in large-scale heterogeneous random networks. Previous work in this area mainly studies the outage probability from the perspective of a given stream, which is inaccurate as it generally overlooks possible interference-driven cross stream signal-to-interference correlation in each communication link. To tackle this issue, in this paper, we focus on a link-level performance evaluation by characterizing the complementary cumulative distribution function (CCDF) of random mutual information (RMI) under heterogeneous interference. We focus on the scenarios that no coordination among transmitters is persuaded, and the receivers do not attempt to cancel out part of interuser interference. Assume that channel state information is known at both the transmitter and receiver of each communication pair, Rayleigh fading, that the singular value decomposition (SVD) is applied to construct pre-coding/post-coding filters for single-user detection, and that transmitted signals of antennas are i.i.d. Gaussian. We first provide accurate expression for the achievable data rate (ADR) of each link, and show that, regardless of the interference power, when transceivers are equipped with equal number of antennas it grows sublinearly with the number of antennas. We then approximate RMI via Gaussian distribution that its mean is the ADR and its variance is derived based on network's parameters. It is seen that the Gaussian approximation is credible even when two streams of data are transmitted. This paper provides various insights regarding the impact of system parameters, including density of transmitters, path-loss exponent, and the number of antennas, on the ADR and CCDF of RMI. We finally spot tremendous benefits of the SVD scheme over other prominent multiplexing systems, including maximum ratio combining, zero-forcing, and diagonal BLAST superstructure with minimum mean square error receivers. [ABSTRACT FROM PUBLISHER]

In multiple-input–multiple-ouput (MIMO) interference channels (IFCs), interference alignment (IA) with zero-forcing (ZF) linear detection can be used to achieve the maximum degrees of freedom (DoFs). However, ZF linear detection usually degrades the performance due to the noise enhancement in practical systems. In this paper, we propose lattice reduction (LR)-aided successive interference cancelation (SIC) in conjunction with IA over lattice for three-user (and extendable to $K$-user) MIMO IFCs in which the interfering signals aligned over the lattices are detected and canceled rather than nulled out. To complete the proposed LR-aided SIC method, the detection ordering and the precoding matrix that minimize the mean square error are also determined. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the problem of spectrum leasing in cognitive radio (CR) networks, while incorporating two advanced physical-layer technologies, i.e., multiple-input multiple-output (MIMO) and distributed interference alignment. We present a cooperative spectrum leasing scheme for primary and secondary users to balance the tension between data transmission and revenue collection/payment. A Stackelberg game is formulated, where the primary user is the leader, and secondary users are followers. With backward induction, we derive the optimal strategies for primary and secondary users that can achieve the unique Stackelberg equilibrium, where no player can gain by a unilaterally changing strategy. We find that spectrum leasing is always beneficial to enhancing the utilities of primary and secondary users. The proposed scheme outperforms a no-spectrum-leasing scheme and a cooperative scheme presented in the literature with considerable gains, which demonstrate the benefits of spectrum leasing and distributed interference alignment and validates the efficacy of the proposed scheme. [ABSTRACT FROM PUBLISHER]

Optimal power allocation (PA) strategies can make a significant rate improvement in secure spatial modulation (SM). Due to the lack of secrecy rate (SR) closed-form expression in secure SM networks, it is hard to optimize the PA factor. In this paper, two PA strategies are proposed: gradient descent (GD), and maximum product of signal-to-interference-plus-noise ratio (SINR) and artificial-noise-to-signal-plus-noise ratio (ANSNR) (Max-P-SINR-ANSNR). The former is an iterative method and the latter is a closed-form solution. Compared to the former, the latter is of low-complexity. Simulation results show that the proposed two PA methods can approximately achieve the same SR performance as the exhaustive search method and perform far better than three fixed PA ones. With extremely low complexity, the SR performance of the proposed Max-P-SINR-ANSNR performs slightly better and worse than that of the proposed GD in the low to medium, and high signal-to-noise ratio regions, respectively. [ABSTRACT FROM AUTHOR]

This paper studies the degrees of freedom (DoF) of two-way $2\times 2\times 2$ MIMO interference networks, a class of two-way four-unicast networks. We first provide upper and lower bounds on the sum DoF of general two-way $2\times 2\times 2$ MIMO interference networks with any number of antennas in each node. We then investigate the special case where all user nodes have $M$ antennas and relay nodes have $N$ antennas, and provide the simplified bounds on the sum DoF. We show that our proposed achievable rate for this special case is higher than the achievable rates recently proposed in. Moreover, for this special case, we obtain the exact DoF $=4M$ when $N \geq 2M$ , and DoF $=4N$ when $M \leq 2N$. [ABSTRACT FROM AUTHOR]

In this paper, we study resource allocation for multiuser multiple-input–single-output secondary communication systems with multiple system design objectives. We consider cognitive radio (CR) networks where the secondary receivers are able to harvest energy from the radio frequency when they are idle. The secondary system provides simultaneous wireless power and secure information transfer to the secondary receivers. We propose a multiobjective optimization framework for the design of a Pareto-optimal resource allocation algorithm based on the weighted Tchebycheff approach. In particular, the algorithm design incorporates three important system design objectives: total transmit power minimization, energy harvesting efficiency maximization, and interference-power-leakage-to-transmit-power ratio minimization. The proposed framework takes into account a quality-of-service (QoS) requirement regarding communication secrecy in the secondary system and the imperfection of the channel state information (CSI) of potential eavesdroppers (idle secondary receivers and primary receivers) at the secondary transmitter. The proposed framework includes total harvested power maximization and interference power leakage minimization as special cases. The adopted multiobjective optimization problem is nonconvex and is recast as a convex optimization problem via semidefinite programming (SDP) relaxation. It is shown that the global optimal solution of the original problem can be constructed by exploiting both the primal and the dual optimal solutions of the SDP-relaxed problem. Moreover, two suboptimal resource allocation schemes for the case when the solution of the dual problem is unavailable for constructing the optimal solution are proposed. Numerical results not only demonstrate the close-to-optimal performance of the proposed suboptimal schemes but unveil an interesting tradeoff among the considered conflicting system design objectives as well. [ABSTRACT FROM AUTHOR]

Tomlinson–Harashima precoded (THP) multiple-input–multiple-output (MIMO) systems are developed to cancel the intersymbol interference (ISI) at the transmitter. However, the THP at least requires perfect channel direction information (CDI) to completely mitigate the interference at the transmitter, which is not practical in the real world. The limited feedback systems are then practically developed to convey the quantized CDI to the transmitter. Using the quantized CDI to conduct the THP, an unavoidable interference degrades the performance at the receiver. In this paper, we investigate the performance degradation resulted from the random vector quantization (RVQ), which is a kind of CDI-based limited feedback mechanism. Here, we measure the performance degradation as the excess mean-squared error (EMSE). Since the formulation of the EMSE is a complicated function of the quantization error, we proposed using the second-order Taylor expansion to derive an analytical result. Simulation results have also verified our proposed analysis, showing that the derived analysis can match the actual EMSE. [ABSTRACT FROM PUBLISHER]

In this paper, we study the codebook size design strategies in the multiple-input–multiple-output (MIMO) broadcast channel (BC) systems. We adopt the nonlinear Tomlinson–Harashima precoder (THP), which is designed by the imperfect channel direction information (CDI) acquired from the random vector quantization (RVQ) feedback mechanism. Under the limitation of the total feedback rate, we flexibly allocate the size of each user's codebook so that the overall channel capacity is maximized. Since the design problem is not convex, directly finding out the optimum allocation of codebook size is not attainable. However, by sophisticatedly using the discrete majorization theory, we can derive the codebook size allocation strategies for the high- and the low-signal-to-noise-ratio (SNR) regions. Interestingly, the results show that the equal size codebook is preferable in the low-SNR region, whereas the codebook allocates the whole available codebook size to a single user in the high-SNR region. Simulations certify the theoretical result of our design. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the sum-rate maximization problem in multiple-input multiple-output interference channels. We design the transmit covariance matrix, associated with each transmitter to maximize the sum-rate of the network when the number of data symbols is unknown. The design problem is nonconvex and then hard to be solved. We devise a semidistributed design methodology according to majorization–minimization technique to deal with the optimization problem. This leads us to a convex quadratically constrained quadratic program at each iteration with a semiclosed form solution. The proposed method is computationally efficient and converges to stationary points of the problem. The fact that the method is based on a distributed processing framework along with relatively low computational burden ( $\mathcal{O}(\max \lbrace M,N\rbrace ^{2.3})$ per iteration with $M$ and $N$ being the number of antennas at the transmitter and receiver, respectively) for the user terminals can make it a potential candidate for practical implementations. Finally, we extend the proposed method for the case with channel estimation errors. Simulation results verify the efficiency of the proposed method, and in a typical scenario we have around 60 times lower run-time when compared to the counterparts of the method. [ABSTRACT FROM AUTHOR]

This paper investigates simultaneous wireless information and power transfer (SWIPT) in the ad hoc network, where access points (APs) with multiple antennas can transfer energy as well as information using a common spectrum resource. The receiving nodes decode the incoming information data (information decoding, ID) and/or harvest the RF energy (energy harvesting, EH), where two different receiving node architectures—time switching (TS) and power splitting (PS)—are considered. By using a stochastic geometry approach, we aim to analyze the transmission capacity and the harvested energy per unit area as performance measures of the SWIPT in the ad hoc network. From the analytical results, we can derive the optimal node densities of ID nodes and EH nodes for TS architectures and, furthermore, optimize the power splitting ratio jointly with the node density for the PS architectures such that the harvested energy per unit area is maximized when the target transmission capacity is given. The proposed node density optimization gives us a useful insight into the design of SWIPT-based ad hoc network, where we can show how densely the APs/nodes can be deployed in a given area and furthermore, find that the ad hoc network with PS receiving nodes outperforms that with TS receiving nodes for a large target transmission capacity, and vice versa. [ABSTRACT FROM AUTHOR]

The evaluation of the coverage probability of multistream multiple-input multiple-output (MIMO) communications in HetNets subject to noise, fading, and intercell interference is undoubtedly intricate. Unfortunately, the current literature misses its comprehensive evaluation, as the effects of noise and cross-stream correlation are often overlooked. Furthermore, computationally friendly expressions of the coverage probability allowing engineering insights and adaptive system design are lacking. For multistream MIMO zero-forcing beamforming, in this paper we tackle these issues by considering scenarios where a receiver is in the coverage if all of its data-streams are successfully decoded. Assuming the max signal-to-interference-plus-noise ratio (SINR) cell association (CA), we adopt the stochastic geometry tools to provide an upper bound and an easy-to-compute closed-form lower bound on the coverage probability, while their accuracies are confirmed against extensive simulations. Our contributions are as follows. We prove that full correlation of data streams of a given link slightly reduces the coverage performance. We show that from a coverage probability perspective, the single stream communication is preferable. We exploit our analysis to explore several pertinent design issues, which have not fully discussed in the literature. Our results demonstrate tradeoffs between densification and multiplexing gains. We, further, see that by appropriately designating feedback channel with modest capacity 8 bits per frame per user, the spatial throughput grows by nearly 180 $\%$ over the conventional 1-bit feedback scenario. Finally, We present important extensions of our analysis to underlay spectrum sharing, practical aspects of the max-SINR CA, and a nonhomogeneous path loss environment. [ABSTRACT FROM PUBLISHER]

In this paper, we study the uplink in a single-cell massive multiple-input–multiple-output system. The base station (BS) is equipped with three antenna arrays, each covering one third of the cell area. Each antenna array comprises a large yet finite number of antennas. The single-antenna users are randomly and uniformly distributed in the cell, transmitting to the BS utilizing full channel inversion power control. All users experience Rician fading. Receiver maximum-ratio-combining is performed at the BS. Under such a setting, we focus on one cell sector and analyze the intrasector interference in a realistic situation where the number of BS antennas is not extremely large compared with the user number. In particular, we show that, due to the line-of-sight (LoS) component of the channel, the interference is partially determined by the angles of arrival of the signals. We approximate the LoS component interference by a Beta mixture. The interference in Rician fading is then modeled as a noncentral chi-square distribution with a random noncentrality parameter, corresponding to the LoS component. The approximate interference distribution can be used to compute signal-to-interference-ratio-dependent metrics such as outage probability and average throughput. [ABSTRACT FROM AUTHOR]

This paper studies the impact of a multiple-input–multiple-output (MIMO) relay on the $K$- user multiple-input–single-output (MISO) interference channel (IC) when the relay has delayed feedback (i.e., delayed channel state information (CSI) or delayed channel output feedback) from each receiver, yet each transmitter has no knowledge about CSI. We first develop a new relay-aided retrospective interference alignment (r-RIA) and characterize the optimal sum degrees of freedom (DoFs) for the $K$- user MISO IC with a MIMO relay by providing a new matching outer bound. It is shown that the sum DoF does not decrease, even in the absence of direct links between transmitters and receivers, as long as $K$ is sufficiently large. We next show that a MIMO relay can provide a sum-DoF gain in the $K$- user MISO IC with delayed feedback to the relay in the absence of CSI at transmitter (CSIT), whereas relaying is shown to be not useful with instantaneous CSIT from the DoF perspective. [ABSTRACT FROM PUBLISHER]

In this paper, we study the performance of space-shift keying (SSK) modulation for multiple-input–multiple-output (MIMO) wireless systems in the presence of multiple-access interference. More specifically, a synchronous multiuser scenario is considered. The main technical contributions of this paper are given as follows: Two receiver structures based on the maximum-likelihood (ML) criterion of optimality are developed and analytically studied, i.e., single- and multiuser detectors. Accurate frameworks for computing the average bit error probability (ABEP) over independent identically distributed (i.i.d.) Rayleigh fading channels are proposed. Furthermore, simple and easy-to-use lower and upper bounds for performance analysis and system design are introduced. The frameworks account for the near–far effect, which significantly affects the achievable performance in multiple-access environments. In addition, we extend the analysis to generalized SSK (GSSK) modulation, which foresees multiple active antennas at the transmitter. With respect to SSK modulation, GSSK modulation achieves higher data rates at the cost of increased complexity at the transmitter. The performance of SSK and GSSK modulations is compared with that of conventional phase-shift keying (PSK) and quadrature amplitude modulation (QAM) schemes, and it is shown that SSK and GSSK modulations can outperform conventional schemes for various system setups and channel conditions. In particular, the performance gain of SSK and GSSK modulations increases for increasing values of the target bit rate and of the number of antennas at the receiver. Finally, we put forth the concept of coordinated multipoint (or network MIMO) SSK (CoMP-SSK) modulation as a way of exploiting network cooperation and the spatial-constellation diagram to achieve high data rates. Analytical derivations and theoretical findings are substantiated through extensive Monte Carlo simulations for many setups. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is a promising transmission technology enabling, essentially, the maximum achievable degrees of freedom (DOF) in $K$-user multiple-input–multiple-output (MIMO) interference channels. The ideal DOF of IA systems have been obtained using independent MIMO channels, which is, usually rarely observed in reality, particularly in indoor environments. Therefore, the data sum rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between MIMO channels decreases the signal-to-noise ratio (SNR) of the received signal after alignment. For this reason, an acceptable sum rate of IA in real MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the distance between network nodes and the separation between the antennas within each node to minimize the spatial correlation. In this paper, we propose to apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection, aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances, while keeping the minimum spatial antenna separation of 0.5 wavelengths within each node. Two selection criteria are considered: maximum sum rate (Max-SR) and minimum error rate (Min-ER). To avoid subcarrier imbalance across the antennas of each user, which is caused by per-subcarrier selection, a constrained per-subcarrier antenna selection is operated. Furthermore, a suboptimal antenna selection algorithm is proposed to reduce the computational complexity of the optimal algorithm. An experimental validation of MIMO-OFDM IA with antenna selection in an indoor wireless network scenario is presented. The experimental results are compared with deterministic channels that are synthesized using hybrid electromagnetic (EM) ray-tracing models. Our performance evaluation shows that the practical feasibility of MIMO-OFDM IA systems is significantly increased by antenna selection in real-world scenarios. [ABSTRACT FROM AUTHOR]

Multiuser orthogonal frequency-division multiplexing (OFDM) and multiple-output multiple-output (MIMO) have been widely adopted to enhance the system throughput and combat the detrimental effects of wireless channels. Interference alignment has been proposed to exploit interference to enable concurrent transmissions of multiple signals. In this paper, we investigate how to combine these techniques to further enhance the system throughput. We first reveal the unique characteristics and challenges brought about by using interference alignment in diagonal channels. We then derive a performance bound for the multiuser (MIMO) OFDM interference alignment system under practical constraints and show how to achieve this bound with a decomposition approach. The superior performance of the proposed scheme is validated with simulations. [ABSTRACT FROM PUBLISHER]

This paper considers the $K$-user multiple-input–single-output (MISO) broadcast channel with delayed channel state information at the transmitter (CSIT) where the base station has only two antennas. Based on the MAT

Named after M. A. Maddah-Ali and D. Tse [1]. [ABSTRACT FROM PUBLISHER]

For massive multiuser multiple input multiple output (MIMO) (MU-MIMO) systems, pilot contamination (PC) and data interference (DI) are two main factors that affect the accuracy of the superimposed pilot (SP) based channel estimation, provided that the channel coherence time is less than the total number of users. In this paper, to tackle the effect of the PC, we propose a block-diagonal Grassmannian line packing (GLP) approach, in which the specific sequences for different cells are first designed based on the GLP, and then are block-diagonally extended to form the SP matrices for the users in different cells. To also alleviate the effect of DI on the channel estimation, with the designed SP matrices, an iterative channel estimation (ICE) method based on Tikhonov regularization is presented. The impact that the proposed ICE method has on the signal-to-interference-plus-noise ratio with matched filtering receiver is theoretically analyzed. Moreover, the optimal power allocation factor to the SP by maximizing the spectral efficiency (SE) of the target cell is also derived. Numerical results show that the proposed ICE method with the designed SP matrices effectively mitigates the effects of the PC and DI, and hence, improves the accuracy of channel estimation and further the SE of the massive MU-MIMO systems. [ABSTRACT FROM AUTHOR]

A major challenge in designing a spectral co-existence between radar and communication systems is how to simultaneously provide efficient utilization of the shared spectrum while maintaining a reliable performance for both systems. Due to its flexibility in using linear independent waveforms and superiority in terms of target detection and estimation, the collocated multiple-input-multiple-output (MIMO) radars provide a paramount capability in realizing spectrum sharing with communication systems. In this paper, we consider the use of joint transmit and receive beamformers for both the MIMO radar and MIMO communication systems. Specifically, we design a two-tier alternating optimization spectrum sharing framework that is based on interference alignment (IA) approach. The effectiveness of spectrum sharing between radar and communication systems is guaranteed by mitigating the mutual interference signals in the shared spectral band. Subsequently, motivated by the excellent performance provided by IA in different wireless network scenarios, we propose a spectrum sharing framework that consists of a main iterative algorithm with two subalgorithms included within its operation. The first subalgorithm is used to maximize the signal-to-interference-plus-noise ratio of the radar system, whereas the second one is utilized to maximize the average sum-rate of the communication system. The main iterative algorithm is proposed to jointly optimize the transmit and receive beamforming filters of both systems by performing alternating optimization between the two subalgorithms. The convergences of the proposed algorithm and its subalgorithms are numerically verified. Simulation results are provided to confirm the superiority of the proposed framework for both systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the transmitter cooperation based topological interference management (TIM) scheme for MIMO Interference Channels (IC), where there is no channel state information beyond only the topology information at transmitters and receivers to cancel the interference. Specifically, for two different scenarios, i.e., there exists a Hamiltonian cycle or a perfect matching in the alignment-feasible graph, we propose different transmitter cooperation based TIM schemes by jointly designing the precoding and decoding matrices and present one theorem to characterize the achievable degrees of freedom (DoF) of the proposed TIM schemes. Moreover, the numeric results show that the DoF of the proposed scheme can be significantly higher than that by the TIM scheme without transmitter cooperation. [ABSTRACT FROM AUTHOR]

In this paper, the performance of an underlay multiple-input multiple-output (MIMO) cognitive radio system is analytically studied. In particular, the secondary transmitter operates in a spatial multiplexing transmission mode, while a zero-forcing detector is employed at the secondary receiver. Additionally, the secondary system is interfered by multiple randomly distributed single-antenna primary users (PUs). To enhance the performance of secondary transmission, optimal power allocation is performed at the secondary transmitter with a constraint on the interference temperature (IT) specified by the PUs. The outage probability of the secondary receiver is explicitly derived in an exact closed-form expression. Also, some special cases of practical interest, including colocated PUs and massive MIMO, are discussed. Further, to mitigate instantaneous excessive interference onto PUs caused by the time-average IT, an iterative antenna reduction algorithm is developed for the secondary transmitter and, accordingly, the average number of transmit antennas is analytically computed. Extensive numerical and simulation results corroborate the effectiveness of our analysis. [ABSTRACT FROM PUBLISHER]

Due to the use of an appropriately designed pulse shaping prototype filter, filter bank multicarrier (FBMC) system can achieve low out of band (OoB) emissions and is also robust to the channel and synchronization errors. However, it comes at a cost of long filter tails, which may reduce the spectral efficiency significantly when the block size is small. Filter output truncation (FOT) can reduce the overhead by discarding the filter tails but may also significantly destroy the orthogonality of FBMC system, by introducing intercarrier interference (ICI) and intersymbol interference (ISI) terms in the received signal. As a result, the signal-to-interference ratio (SIR) is degraded. In addition, the presence of intrinsic interference terms in FBMC also proves to be an obstacle in combining multiple-input multiple-output (MIMO) with FBMC. In this paper, we present a theoretical analysis on the effect of FOT in an MIMO-FBMC system. First, we derive the matrix model of MIMO-FBMC system, which is subsequently used to analyze the impact of finite filter length and FOT on the system performance. The analysis reveals that FOT can avoid the overhead in the time domain but also introduces extra interference in the received symbols. To combat the interference terms, we then propose a compensation algorithm that considers odd and even overlapping factors as two separate cases, where the signals are interfered by the truncation in different ways. The general form of the compensation algorithm can compensate all the symbols in a MIMO-FBMC block and can improve the SIR values of each symbol for better detection at the receiver. It is also shown that the proposed algorithm requires no overhead and can still achieve a comparable bit error rate (BER) performance to the case with no filter truncation. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) has been recognized as a promising technique to obtain large multiplexing gain in multiple-input–multiple-output (MIMO) interference channels. Most existing IA schemes require global channel state information (CSI) at the transmitter to design precoding vectors and, thus, result in significant capacity overhead in the feedback link. To reduce the feedback overhead, in this paper, we investigate the IA scheme employing differential CSI feedback over time-correlated MIMO channels. Specifically, we analyze the achievable sum-rate performance using differential feedback and derive the minimum differential feedback rate to achieve the maximum multiplexing gain. We also provide the upper bound of the sum-rate performance loss due to the limited differential feedback rate. Finally, the analytical results are verified by simulations in a practical IA scheme with differential CSI feedback using Lloyd's quantization algorithm. [ABSTRACT FROM PUBLISHER]

This paper investigates the interference statistics and system performance of a finite multiple-input–multiple-output (MIMO) ad hoc network. A finite network contains a finite number of nodes in a finite region. For such a network, the binomial point process, rather than the ubiquitously employed Poisson point process, is adopted to characterize the spatial node distribution. Reception techniques such as the maximal ratio combining (MRC) and zero forcing (ZF) are employed at the receiver, around which a guard zone is deployed. Either spatial multiplexing or antenna selection is employed at the transmitter side, depending on the availability of feedback. The moment generating functions of the aggregate interference power are first derived, based on which the moments of interference and the outage probability of a test link are obtained. It is shown that the full diversity provided by the channel can be achieved by single-stream transmission, including transmit antenna selection. A network performance measure, i.e., the average network throughput, is also analyzed. Simulations are provided to complement the analysis. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the performance analysis of the maximum eigenmode beamforming (MEB) scheme with equal power allocation (EPA) over practically coded multiple-input multiple-output (MIMO) multiple-access channels (MACs). Both the scenarios of perfect and imperfect channel state information (CSI) at the transmitters (CSIT) are considered. Analytical and numerical results show that MEB with EPA can achieve significant power savings and is less sensitive to CSIT error than other alternatives. [ABSTRACT FROM PUBLISHER]

This paper investigates the performance of multihop virtual multiple-input–multiple-output systems (V-MIMO), based on the concept of virtual antenna array (VAA), in the presence of random location of nodes. Nodes are supposed to be distributed according to a Poisson point process. Random fluctuations are considered, and the channel model takes both slow and fast fading into account. Performance is evaluated in terms of outage probability, which is defined as the probability that the ergodic capacity between the source and the destination is smaller than a given threshold. We investigate the impact of a random distribution of nodes on the overall performance. The role played by the interference, when some reuse of radio resources is considered for inter-VAA communication, is also investigated. [ABSTRACT FROM PUBLISHER]

This paper analyzes the average bit error rate (BER) of multiple-input–multiple-output (MIMO) systems in transmit-correlated Rayleigh flat-fading channels. The receiver scheme is based on the minimum mean square error (MMSE) criterion, and the input may be precoded to optimize the communication. Accurate closed-form formulations for the average BER are derived. [ABSTRACT FROM PUBLISHER]

Full-duplex (FD) multiple-input multiple-output relaying has been considered an effective scheme to increase the spectral efficiency for wireless communications. As known, the main problem for the FD system is the cancellation of loop interference (LI). In this paper, we propose using the joint source/relay precoding to reduce the influence of LI. Therein, linear precoders are used at the source and relay, while the minimum mean-squared-error receiver is adopted at the destination. The joint precoder design is complicated when spatial multiplexing is exploited for signal transmission. To solve the problem, we propose an iterative method in which the original problem is split into two subproblems. With some matrix properties, we then show that each subproblem can be formulated as a convex optimization. Finally, a closed-form solution can be obtained with the Karush–Kuhn–Tucker conditions. Using a mean-squared-error upper bound, we also propose a low-complexity method to reduce the computational complexity. The proposed precoders have closed-form expressions, which is a great advantage in real-world implementation. Simulation results show that the proposed methods significantly outperform existing ones. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the interference alignment (IA) for the multiple-input–multiple-output (MIMO) multicell downlink networks in the context of a square channel matrix. We propose a novel joint user grouping and base station (BS) association algorithm. Furthermore, we design the transmit and receive beamforming matrices in closed forms by using a generalized eigenvalue decomposition (GEVD)-based IA scheme, which can exploit the special structure of a square channel matrix against the existing algorithm. Moreover, we provide three theorems to characterize the maximum achievable degrees of freedom (DoF) of the proposed GEVD-based IA scheme. Compared with the existing IA scheme, the proposed GEVD-based IA scheme can reduce the dimension of subspace occupied by the intercell interference (ICI) more efficiently, hence providing achievable DoF higher than or equal to that of the existing IA scheme. [ABSTRACT FROM AUTHOR]

This paper characterizes the exact spatial Degrees of Freedom (DoF) region of the two-user multiple-input–multiple-output two-interfering multiple-access channels (2-IMACs), which models the uplink transmission in cellular networks, for three scenarios. The first scenario is the 2-IMAC without cognition, for which the achievability is generalized for more than two transmitters in each multiple-access channel. The two-user 2-IMACs' DoF regions are also derived for two different genie-aided cognition scenarios. Here, zero forcing by transmitters and interference alignment are studied in a network with more than two transmitters, whereas previous works dealt with two-transmitter networks. We also perform a comparative analysis on the DoF of the three scenarios. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is widely regarded as a promising interference management technique for wireless networks and its potential is most profound in interference-intensive environments. This motivates us to study IA for multicast communications in multihop MIMO networks, which are rich in interference by nature. We develop a set of linear constraints that can characterize a feasible design space of IA for multicast communications. The set of linear constraints constitutes a simple mathematical model of IA that allows us to conduct cross-layer multicast throughput optimization in multihop MIMO networks, but without getting involved into the onerous signal design at the physical layer. Based on the mathematical model of IA, we formulate a multicast throughput maximization problem and develop an approximation solution that can achieve $(1-\varepsilon)$ -optimality. Simulation results show that the use of IA can significantly increase the multicast throughput in multihop MIMO networks and the throughput gain increases with the volume of multicast traffic and the number of antennas. [ABSTRACT FROM AUTHOR]

To achieve the full multiplexing gain of a $K$-multiuser multiple-input–multiple-output (MIMO) overlay cognitive radio (CR) network, a distributed opportunistic interference alignment (DOIA) technique using a new beamforming algorithm, namely, threshold-based beamforming (TBF), is proposed. The MIMO overlay CR system consists of one primary user (PU) and $K$ secondary users (SUs) where the local channel state information is available at both the transmitters and receivers of SUs. Assuming that the receiver and the transmitter of the PU have perfect knowledge of their own channel matrix, the PU uses a maximum eigenmode beamforming (MEB) scheme for its data transmission to release some of its eigenmodes for the SUs. For this virtual cooperation, the SUs align their transmitted signals to the spatial directions (SDs) associated with the unused PU's eigenmodes to ensure orthogonality between the links of the PU and the SUs. In addition, the MEB scheme overcomes the limitation of the conventional water-filling power allocation (WPA) in releasing the PU's eigenmodes for the SUs at high signal-to-noise ratios (SNRs). A noniterative and distributed power-allocation strategy, namely, TBF, is proposed, in which the SUs' links with a maximum eigenvalue above a certain threshold transmit data at full power, and the rest remain silent. This protocol, along with the MEB scheme, enables the MIMO overlay CR system to enhance the throughput of the network described as the average sum rate of both the PU and SUs. The proposed DOIA-TBF protocol allows the opportunistic SUs to use the same frequency band of a preexisting PU and guarantees that no interference is imposed on the PU's performance for such a MIMO overlay CR system. [ABSTRACT FROM PUBLISHER]

The maximum–minimum-throughput-based power assignment (MMTPA), which results in the maximum–minimum throughput among all secondary users (SUs) while assuring the quality of service (QoS) of each primary user (PU), is proposed for multiple-input–multiple-output (MIMO) systems in cognitive radio (CR) networks. We first derive the capacity bound of the MIMO system under cochannel interference and use this capacity bound to quantify the throughput. Instead of employing the traditional optimization technique, we present a proposition to simplify the optimization of the power assignment. In particular, in the uplink of the infrastructure-based CR network, the problem can be reduced so that the MMTPA only has to optimize the transmit power of the representative SU and keep the ratio of the transmit power of each SU to that of the representative SU constant. For comparison, we also propose two other power assignments, namely, the equal power assignment (EPA) and the iterative power control (IPC). As expected, we found from simulation results that MMTPA outperforms EPA and IPC in the minimal throughput among all SUs. [ABSTRACT FROM PUBLISHER]

We consider a multicast scenario that involves an ad hoc network of cochannel multiple-input–multiple-output (MIMO) nodes in which a source node attempts to share a streaming message with all nodes in the network through some predefined multihop routing tree. The message is assumed to be broken down into packets, and the transmission is conducted over multiple frames. Each frame is divided into time slots, and each link in the routing tree is assigned one time slot in which to transmit its current packet. We present an algorithm for determining the number of time slots and the scheduling of the links in these time slots to optimize the connectivity of the network, which we define to be the probability that all links can achieve the required throughput. In addition to time multiplexing, the MIMO nodes also employ beamforming to manage interference when links are simultaneously active, and the beamformers are designed with the maximum connectivity metric in mind. The effects of outdated channel-state information are taken into account in both the scheduling and the beamforming designs. We also derive bounds on the network connectivity and sum transmit power to illustrate the impact of interference on network performance. Our simulation results demonstrate that the choice of the number of time slots is critical in optimizing network performance and illustrates the significant advantage provided by multiple antennas in improving network connectivity. [ABSTRACT FROM PUBLISHER]

We consider the detection of multiple cochannel single-carrier spatially multiplexed data streams. To this end, we propose a hybrid time–frequency-domain decision feedback equalizer, which performs parallel detection of the data streams. A practical parameter estimation algorithm for these receivers is developed, which estimates the MIMO channel in parallel as a set of effective channel vectors. To avoid interference cancellation, we develop a two-stage frequency-domain (FD) forward section that implements linear cochannel interference (CCI) suppression in cascade with equalization utilizing estimated channel-state information. The resulting receiver architecture outperforms interference-cancellation-based equalizers in the presence of channel estimation errors. Furthermore, all transmitted data streams achieve equal diversity gains. [ABSTRACT FROM PUBLISHER]

We examine the application of transmit precoding in multiuser multi-input–multi-output (MIMO) communication systems with maximum ratio combining (MRC) receivers. In many multiuser applications, the maximum-likelihood or minimum mean-square error (MMSE) receivers can be prohibitive to implement due to their high implementation complexity. We examine the performance of the system with simple MRC receivers and carefully selected precoders, which are designed to compensate the lack of high-complexity receivers, at the transmitter side. We examine the sum MSE minimization and signal-to-interference-plus-noise ratio (SINR) balancing frameworks for the selection of precoders. The performance of two frameworks with MRC receivers are compared between themselves as well as with their counterparts implementing MMSE receivers. It has been observed that the SINR balancing framework with simple MRC receivers has little performance loss in comparison with the MMSE receivers with a proper selection of precoders. [ABSTRACT FROM PUBLISHER]

A new precoder design scheme, called the signal-controlled-leakage-noise ratio (SCLNR), is proposed. The proposed SCLNR precoder is designed to enhance the data rate and harvesting energy simultaneously. Specifically, the proposed SCLNR precoder is designed to increase the leakage signal toward energy users and decrease leakage signal toward data users, and can be attained in a closed-form solution. Numerical results are provided to evaluate the performance of the proposed SCLNR precoder for simultaneous wireless-information and power-transfer systems. The proposed SCLNR precoder achieve efficient performance compared with the precoder obtained from complicated iterative algorithm in terms of the computational complexity. The proposed SCLNR precoder outperforms a precoder that uses conventional signal-to-leakage-and-noise ratio based precoder and block diagonalization precoder for data users and energy beamformers for energy users in terms of the rate–energy region. [ABSTRACT FROM AUTHOR]

In massive multiple-input multiple-output (MIMO) crowded networks, the random access (RA) performance of strongest-user collision resolution (SUCRe) protocol can be improved by replacing the hard decision retransmission rule by a soft decision one, so that each user equipment (UE) decides to retransmit or not its pilot sequence with a suitable probability. We obtain this probability for each UE according to the probability of this UE being the strongest contender, while also proposing an analytical approximated probability expression for this event. Hence, the $k$ th UE is able to calculate the probability of itself being the strongest contender in a pilot collision, choosing to retransmit or not its RA pilot in the next step of the protocol according to this probability, without requiring any excessive complexity or additional overheads. Our numerical results demonstrate significant improvements in comparison to the original SUCRe protocol, while maintaining its favorable feature of being a decentralized and uncoordinated approach. [ABSTRACT FROM AUTHOR]

Over the last decade, the ever-growing demand for asymmetric uplink (UL) and downlink (DL) traffic in cellular networks have made the necessity of dynamic time-division duplex (TDD). However, it is plagued by the cross-link interference of adjacent cells. To suppress it, we consider dynamic TDD with massive multiple-input multiple-output (MIMO). For a highly realistic system model, we consider the transceiver noise at the base station (BS), which would further aggravate the coupling between DL and UL. By using random matrix theory, we derive tight deterministic equivalents of the UL and DL achievable rates with a matched filtering receiver and maximum ratio transmission precoder. Exploiting these deterministic equivalents further, we analyze cross-link interference and transceiver noise, and then prove that their effects both scale down as $\mathcal O(M^{-1})$ , thus their elimination is possible by massively increasing the number of antennas. Consequently, the UL–DL decoupling would be achieved in dynamic TDD systems by combining massive MIMO, which is a desirable feature in future cellular networks. Based on the analysis results, we also propose a power control scheme for maximizing the total sum rate, which is decoupled into two tractable geometric programming problems. The effectiveness of this power control is validated by extensive simulation results. [ABSTRACT FROM AUTHOR]

This correspondence proposes a novel multiuser computational offloading scheme for a fog-based scenario. Specifically, a controlling user (CU) distributes its computational tasks to multiple trusted helping users (HUs) by exploiting both nonorthogonal multiple access (NOMA) and beamforming. First, social relationships between the CU and HUs are exploited for the selection of trusted HUs. Then, the HUs having sufficient computing resources and high social trust are selected and grouped into multiple pairs. For the sake of improving the spectral efficiency, NOMA is invoked for simultaneously supporting several HUs. Meanwhile, a process of zero-forcing beamforming is used by the CU to completely eliminate the interpair interference, hence further enhancing the sum rate. By analyzing the achievable rate and energy consumption of the uplink and downlink transmission, an energy consumption minimization problem is formulated subject to the constraints of signal-to-interference plus noise ratio and transmission latency. We design a user-pairing and resource allocation algorithm for successively optimizing the power allocation and computational task distribution, while satisfying the classic Karush–Kuhn–Tucker conditions. Our numerical results demonstrate that by combining the social relationships, the computational capacities, and the channel conditions, the proposed multiuser computational offloading scheme relying on social trust, NOMA, and beamforming improves the energy consumption, sum rate, and transmission latency. [ABSTRACT FROM AUTHOR]

Interrelay interference (IRI) is known to degrade the performance of virtual full-duplex (FD) relaying schemes. Although interference avoidance and cancelation strategies have been proposed in the existing literature, most studies reflect the traditional information theoretical viewpoint of interference as a degrading factor on information decoding (ID). However, from energy harvesting (EH) perspective, the IRI could be beneficial. This motivates the study of simultaneous wireless information and power transfer in decode-and-forward multiple input multiple output virtual FD relaying system, where the IRI serves as an additional source of energy to the relay. To manage the degrading effect of the IRI on the ID receiver, transmit antenna selection is proposed at the relay. In addition, precoding matrices that optimize the ID and EH receivers are jointly designed. The simulated results show that although IRI could be a degrading factor from the information viewpoint, it can be properly managed and exploited for EH at the relay while maintaining the end-to-end data rate. In addition, the results show that the end-to-end information rate and harvested energy can be simultaneously achieved using the proposed precoders. [ABSTRACT FROM AUTHOR]

We tackle the problem of minimizing the maximum expected delivery time of all transmission pairs in 60 GHz mmWave networks. The network is dual-hop with multiple transmitter-receiver pairs, relays, and a centralized controller (termed PicoNet coordinator). We jointly optimize relay and link selection for the transmitter–receiver pairs to minimize delivery time, while the reflected non-line-of-sight transmission links are exploited to get around obstacles. To reduce computational complexity, we develop a decomposition principle to transform the joint-optimization problem into a link selection subproblem and a relay assignment subproblem when there are a sufficient amount of relays. A tight performance bound for the proposed algorithm is proved. We also develop a heuristic scheme to handle the case when there are no enough relays. The superior performance of our proposed algorithms is validated with extensive simulations and comparisons with benchmark schemes. [ABSTRACT FROM AUTHOR]

An interference alignment (IA) transceiver design scheme for multiple-input–multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI). [ABSTRACT FROM AUTHOR]

A cooperative hybrid cognitive radio (CR) network is proposed to simultaneously operate on a dedicated licensed band and a secondary band. The licensed band is used for communications between a base station (BS) and mobile CR users, whereas the secondary band is used to facilitate the licensed band communication by coordinating multiple CR users to form distributed virtual antenna arrays (VAAs). The capacity of the proposed CR network is studied at both the link and system levels. At the link level (single VAA case), we present an amplify-and-forward-based cooperative signaling scheme that employs power control to prevent harmful noise propagation. The resulting virtual multiple-input–multiple-output (MIMO) link capacity is derived and compared with the real MIMO system. At the system level (multiple VAAs case), the system capacity is derived as a function of multiple parameters, including the primary user density, CR user density, primary exclusion region radius, and VAA radius. Under an average interference power constraint, the maximum system capacity is further calculated by solving an optimization problem with adjustable system parameters. Numerical studies reveal that the proposed cooperative hybrid CR network has a fundamental advantage over a pure CR network by being insensitive to the characteristics of the coexisting primary network. This merit, however, relies on a high CR user density and a wide bandwidth of the secondary band. [ABSTRACT FROM PUBLISHER]