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In this paper, we examine orthogonal space–time block coding with receiver maximal ratio combining (OSTBC/MRC) and selection combining (OSTBC/SC) in multiple-input–multiple-output (MIMO) decode-and-forward (DF) relay networks with underlay spectrum sharing, considering optimal and suboptimal cases. The secondary network under consideration is equipped with multiple correlated antennas at the source, the relay, and the destination. On the other hand, the primary network is composed of $L$ primary users (PUs), each of which is equipped with multiple correlated antennas. For the considered underlay spectrum sharing, the transmit power condition is related by an interference limit on the primary network and the maximum transmission power in the secondary network. In particular, new exact expressions for the outage probability of the adopted system models are obtained. Moreover, simple asymptotic expressions for the outage probability are provided to enable the characterization of the achievable diversity orders and coding gains. To enhance the secondary network performance, optimal power allocation (PA) between the secondary source and the secondary relay is obtained based on the asymptotic outage probability under the constraints of total allowable transmit power at the secondary user (SU) and maximum allowable interference power limit at the PU. The derived analytical formulas herein are supported by numerical results to clarify the main contributions. [ABSTRACT FROM AUTHOR]

Multicell coordinated beamforming (CB) can mitigate intercell interference (ICI). However, existing work on CB focuses on systems that maximize overall throughput. This paper considers CB for systems with multiple receive antennas and further extends the CB to multiuser and multistream transmission. We consider fairness and pay close attention to cell-edge users. CB that maximizes the harmonic sum of signal-to-interference-plus-noise ratio (SINR) can be derived into a low-complexity algorithm that favors cell-edge users. Two iterative algorithms are developed. From the simulation results, the proposed algorithms can provide a better fifth-percentile user throughput compared with the CB algorithms minimizing mean square error, maximizing uplink SINR, and maximizing weighted sum rate. Furthermore, the computational complexity of the proposed algorithms is significantly lower than that maximizing the minimum SINR of users. [ABSTRACT FROM AUTHOR]

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]

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]

In this paper, we propose a general framework to evaluate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in cognitive radio networks (CRNs). The proposed framework is discussed in three typical CRN paradigms: underlay CRNs (UCRNs), overlay CRNs (OCRNs), and interweave CRNs (ICRNs). The EE–SE relation for three CRNs is expressed in the closed-form formulation, in which the optimal (suboptimal) EE solution as the function of SE is deduced with the corresponding limits. The theoretical analysis and numerical results indicate that the EE–SE relation in CRNs is not contrary, i.e., an optimal EE–SE tradeoff can be achieved. The proposed framework provides a useful guidance in the design of practical green CRNs. [ABSTRACT FROM AUTHOR]

In this paper, we consider time-domain vector perturbation (TDVP) in a large-system limit when channel state information (CSI) is imperfect due to pilot contamination, and we derive the system's achievable sum rate per cell. We use random matrix methods to avoid time-consuming Monte Carlo simulations. Numerical results show that, in general, linear precoding ensures a higher sum rate than TDVP in the massive multiple-input–multiple-output (MIMO) regime. [ABSTRACT FROM AUTHOR]

This paper considers a two-cell uplink cochannel multiple-input–multiple-output (MIMO) network with users sequentially arriving at the network. We study the problem of sequential base-station (BS) selection for the users, with the selection criterion based on the degrees of freedom (DoFs) available for the new arriving user. We find that different sequential BS selections affect individual and network performance in terms of the individual and network sum DoF, as well as the number of admissible users in the network. We propose a method to build the tree structure for sequential BS selection, which carries trellis information for individual and system-wide selections. The properties of the tree are analytically studied. It turns out that by adopting an interference coordination strategy based on the concept of interference alignment (IA), better individual and network performance can be achieved. Simulation compares the proposed DoF-based BS selection and traditional BS selection schemes and highlights the advantages of the proposed scheme. [ABSTRACT FROM PUBLISHER]

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]

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 user selection (US) strategies for a multiple-input–multiple-output (MIMO) cognitive radio (CR) downlink network, where the r-antenna underlay CR secondary users (SUs) coexist with a primary user (PU), and all terminals are equipped with multiple antennas. Two main scenarios are considered: 1) The t-antenna cognitive base station (CBS) has perfect or partial channel state information at the transmitter (CSIT) from the CBS to the PU receiver (RX), and 2) the CBS has absolutely no PU CSIT. For these scenarios, we propose and evaluate multiple SU selection schemes that are applicable to both best-effort PU interference mitigation and hard interference temperature (IT) constraints. The computational complexity of the proposed schemes can be significantly smaller than that of an exhaustive search with negligible performance degradation. For the selection of C SUs out of K, whereas an exhaustive search is on the order of \mathcal{O}(\binom{K}{C}C^4r^3). When t$ and r$ are of the same order, the computational complexity of the proposed scheme can be \binom{K}{C}C^4/K times smaller. Mathematical complexity analysis and numerical simulations are provided to show the advantage of our schemes. [ABSTRACT FROM PUBLISHER]

This paper presents a coherent scheme to optimize an in-band full-duplex multiple-input–multiple-output (MIMO) relay via beamforming and transmit power allocation in a two-hop single-input–single-output (SISO) link under full channel knowledge and perfect hardware assumptions. First, we derive in closed form the optimal pair of transmit power and receive filter for a fixed transmit filter by unifying the minimum-mean-square-error (MMSE) filtering with the SISO-equivalent power allocation, as an iterative approach is not guaranteed to converge to global optimum. Second, we propose a heuristic algorithm to approximate the optimal transmit filter for a fixed receive filter. Furthermore, we study the well-known null-space projection constraint and derive a singular value decomposition (SVD)-based solution for the arbitrary-rank self-interference channel by generalizing the optimal solution under the assumption of rank-1 self-interference channel. Finally, we combine these solutions into a partially iterative algorithm in order to address the global optimization as our observations justify that some of the aforementioned schemes converge to the optimal solution under certain criteria. The numerical analysis of the proposed iterative algorithm demonstrates close-to-optimal performance relative to the theoretical upper bound of the end-to-end link in terms of maximum achievable throughput. [ABSTRACT FROM PUBLISHER]

Massive multiple-input–multiple-output (MIMO) antenna system implies the use of a large number of base station (BS) antennas to serve a relatively small number of user terminals (UTs) for extraordinary spectral efficiency. However, its performance is limited by pilot contamination due to unavoidable reuse of pilot sequences from UTs in different cells. In this paper, we analyze the performance of massive MIMO zero-forcing (ZF) systems using the time-shifted pilot scheme, which was known to combat pilot contamination effectively using conjugate beamforming if there is a very large number of antennas. We derive expressions for achievable sum rates and the signal-to-interference-plus-noise ratios (SINRs) of forward and reverse links if the number of BS antennas is finite. Then, the impact of system parameters, such as cell radius, transmit power, group number (a parameter related to the time-shifted pilot scheme), BS antenna number, etc., on the system performance are revealed. Our model embraces a series of previous works as special cases. Moreover, we compare the performance of conjugate and ZF precoders, from which a simple but effective large-scale fading-based UT scheduling scheme is proposed to enhance the system throughput. [ABSTRACT FROM PUBLISHER]

This paper focuses on precoding design for sum-rate maximization while considering the effects of residual self-interference for multiuser multiple-input–multiple-output (MU-MIMO) full-duplex (FD) systems. The problem formulation leads to a nonconvex matrix-variable optimization problem, where we develop two efficient sum-rate maximization algorithms using sequential convex programming (SCP), namely, the difference of convex functions (DC)-based and the sequential convex approximations for matrix-variable programming (SCAMP) algorithms. In addition, we derive the achievable sum rate under the effect of residual self-interference. Simulation results show that, even in cases of high self-interference and high estimation error, the SCAMP algorithm provides approximately 20%–30% sum-rate improvements over both conventional optimized half-duplex (HD) transmission and the existing state-of-the-art FD algorithm in a wide range of scenarios. Finally, the convergence results indicate that the DC-based algorithm tends to initially give the best performance; however, at convergence, the SCAMP algorithm tends to significantly outperform the other algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we consider unicast/multicast multicell cooperative transmission with interference among users/user groups. In this context, we derive the optimal minimum variance distortionless response (MVDR)-based successive minimum variance beamforming (SMVB) scheme that achieves a superior sum-rate performance compared with the block diagonalization scheme. Subsequently, we derive an optimal joint power allocation and broadcast beamforming scheme for multicell cooperative broadcast transmission for a pooled power constraint at the base stations. This scheme is extended to include per base station power constraints by formulating it as a relaxed semi-definite program (SDP). We also consider the multicell cooperative uplink scenario and derive a successive multiuser (MU) uplink beamforming (SMUB) scheme that maximizes the signal-to-interference-plus-noise ratio (SINR) of each user. Next, we consider imperfect channel state information (CSI) and derive a robust beamforming scheme for the downlink, based on minimizing the worst-case interference by formulating it as a second-order cone program. It is demonstrated that the corresponding robust beamformer for the uplink transmission can be derived by employing the multidimensional covariance fitting approach. Simulation results are presented to demonstrate the superior sum-rate performance of the proposed multicell transmission schemes. The performance is also compared with several bounds for cooperative multicell scenarios. [ABSTRACT FROM AUTHOR]

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 considers limited feedback for a two-cell interfering multiple-input–multiple-output multiple-access channel (MIMO-MAC). We propose a QR decomposition-based interference alignment (QRD-IA) scheme for efficient limited feedback and investigate the conditions for the antenna configuration. We characterize the interference leakage caused by quantization error as a function of the number of feedback bits. To minimize the interference leakage, we further propose a quantized-precoder-based IA (QP-IA) scheme by modifying the proposed QRD-IA scheme. By characterizing the interference leakage of the QP-IA scheme, we investigate the number of feedback bits to maintain the degrees of freedom (DOFs) in the two-cell interfering MIMO-MAC and a feedback bit allocation algorithm to improve the sum rate. From simulation results, we demonstrate that our proposed schemes can provide better sum-rate performance than the existing scheme using the same number of feedback bits, and our feedback bit allocation algorithm provides a higher sum rate compared with equal feedback bit allocation. [ABSTRACT FROM PUBLISHER]

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]

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]

This paper addresses the problem of coordinated beamforming across a group of base stations (BSs) and frequency slots in the downlink of a multiple-input multiple-output (MIMO) orthogonal frequency-division multiple-access (OFDMA) cellular network. Three figures of merit are considered for system design under a per-BS power constraint: 1) the weighted sum of the rates (WSR) on the frequency slots of the coordinated BSs; 2) the global energy efficiency (GEE), defined as the ratio between the network sum rate and the corresponding consumed power; and 3) the weighted sum of the energy efficiencies (WSEE) on the frequency slots of the coordinated BSs. The Karush–Kuhn–Tucker (KKT) conditions of the considered optimization problems are first derived to gain insight into the structure of the optimal beamformers. Then, we propose a suboptimal design method that can be applied to all considered figures of merit. Numerical results are provided to assess the performance of the proposed beamforming strategies. [ABSTRACT FROM PUBLISHER]

Recently, heterogeneous network (HetNet) has been introduced as an appropriate strategy to cope with the explosive growth of wireless traffic. To address the issue of severe interference in the HetNet, we can consider interference alignment (IA), which achieves the maximum degrees of freedom (DOFs) in multiple-input–multiple-output (MIMO) interference channels (ICs). However, an anticipated performance of the MIMO IA is difficult to be clarified, particularly with different numbers of antennas across the nodes when designing an appropriate system. In this paper, we thus study antenna configurations for the three-user MIMO IA with respect to the intended data stream tuple, i.e., DOF. For simple analysis, we consider two-tier network with two types of data stream numbers in a system. First, the dimension of the subspace occupied by interference is derived by aligning the interference in the signal space of the MIMO IA. After this, the suitable numbers of antennas are computed depending on the transmitted data stream numbers. Our obtained results provide an insight on how the performance of the MIMO IA is affected as the system configurations change. Furthermore, we discuss how to maximize the performance of such systems when the available numbers of antennas are finite. The actual simulations with an iterative IA confirm the validity of our derived results. [ABSTRACT FROM PUBLISHER]

In this paper, a novel unified transmission framework in the context of both decode-and-forward (DF) and amplify-and-forward (AF) protocols was proposed for a two-hop multiple-input–multiple-output (MIMO) alternate half-duplex (HD) relaying system with $M$ antennas for each node, which can achieve the maximum M$ degrees of freedom (DoFs) of the system, compared with the existing interference alignment (IA) schemes that can only get \3M/\4 DoF. Furthermore, the proposed schemes require only two relays against three relays invoked in the existing IA schemes. Moreover, the proposed schemes are valid for the cases where the number of antennas $M$ can be either even or odd, whereas the existing IA schemes can only apply for an even number of antennas $M$. [ABSTRACT FROM PUBLISHER]

Linear decoding of space–frequency block codes (SFBCs) based on the Alamouti structure with orthogonal frequency-division multiplexing (OFDM) requires the channel to be constant across two consecutive tones. However, time-dispersive multipath fading channels exhibit frequency-selective behavior wherein the channel across two tones will vary. This paper provides analytical tools for evaluating the performance of SFBCs with OFDM in frequency-selective channels. The analysis uses the average signal-to-interference-plus-noise ratio (SINR) as a sufficient statistic to describe the performance of SFBCs in frequency-selective channels. A unified formula is derived to characterize the channel correlation between two consecutive tones for various frequency-selective channels. A closed-form solution of the average SINR is obtained, which takes into account imperfect channel estimation and frequency selectivity. An interpolation method of the channel estimate is proposed, which is shown to improve the bit-error-rate performance by 3 dB at a high SNR. The accuracy of the theoretical analyses is verified by numerical simulations under multipath channels such as the International Telecommunications Union (ITU) pedestrian and vehicular models. [ABSTRACT FROM PUBLISHER]

Wireless local area networking technologies are widely used in communication-based train control (CBTC) systems, where handoff latency is the key factor affecting the transmission performance. A multiple-input–multiple-output (MIMO)-assisted handoff (MAHO) scheme for CBTC systems is proposed in this paper to reduce handoff latency. During the handoff procedure, the mobile station (MS) communicates with the serving access point (AP) and the candidate AP concurrently with handoff signaling transmitted by one antenna and data packets transmitted by another one so that the station can handoff from one to the other without interrupting data transmission. The interference is canceled by a zero-forcing algorithm in the uplink (UL) and by space–time block code (STBC) interference cancelation algorithms in the downlink. The handoff performance, including transmission delay of train-control-related information due to handoff, the frame error rate (FER) of the handoff signaling, the error-free period, and the required intersite distance, are analyzed and compared with traditional break-before-make schemes. The results show that the MAHO scheme can significantly reduce the handoff latency of CBTC services and that the FER of the handoff signaling is lower than traditional schemes when the data rates are no more than 13 Mb/s. [ABSTRACT FROM PUBLISHER]

We consider the uplink transmission in multiuser wireless systems with multiple single-antenna transmitting users and a multiantenna receiver. We address two problems in this paper. The first problem is user admission, i.e., given a large number of users, how to admit the maximum number of users that can simultaneously satisfy quality of service (QoS) and power constraints. The second problem is how to distribute the data among the users when they are allowed to share data before transmission. The aim is to minimize the total data exchange cost. Such a problem is called user clustering. We formulate those problems into sparsity-maximization problems, which are NP-hard. Inspired by compressive sensing techniques, we propose a common framework to tackle those problems by first applying the \ell1 -norm relaxation and then solving them with convex optimization methods. Simulations show that the proposed algorithms achieve excellent performance. For user admission, the numbers of admitted users by the proposed algorithms are close to the optimum numbers of admitted users obtained by exhaustive search (ES) . For user clustering, the total data exchange cost is reduced by more than 10% after only a few iterations. When the QoS requirement is low, the user data exchange can be avoided using the proposed method, which achieves the optimum result obtained by ES. [ABSTRACT FROM PUBLISHER]

In this paper, we deal with resource allocation in the downlink of spatial multiplexing multiple-input–multiple-output (MIMO)-orthogonal frequency-division multiple-access (OFDMA) systems. In particular, we concentrate on the problem of jointly optimizing the transmit and receive processing matrices, the channel assignment, and the power allocation with the objective of minimizing the total power consumption while satisfying different quality-of-service (QoS) requirements. A layered architecture is used in which users are first partitioned in different groups on the basis of their channel quality, and then channel assignment and transceiver design are sequentially addressed starting from the group of users with most adverse channel conditions. The multiuser interference among users belonging to different groups is removed at the base station (BS) using a Tomlinson–Harashima precoder operating at user level. Numerical results are used to highlight the effectiveness of the proposed solution and to make comparisons with existing alternatives. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new three-user network information flow model, referred to as the triangular multiple-input–multiple-output (MIMO) relay (TMR) channel, which consists of three users and three relays equipped with nU and nR antennas, respectively. Each user sends two independent messages to the other two users via the adjacent relays in two time slots, which are referred to as the multiple-access and broadcast stages. We derive a novel simultaneous signal and interference alignment for the proposed TMR channel in a scenario where there are fewer antennas at each relay than at each user (nR < nU ) . An optimized pseudo-inverse scheme based on an efficient gradient projection algorithm is proposed to solve the simultaneous alignment problem. By deriving a gradient over weighted sum-rate maximization and applying a gradient descent method, the optimal beamforming vectors are obtained to maximize the effective signal-to-noise ratios. Furthermore, to obtain rapid convergence speed and reduce computational complexity, we introduce a quasi-Newton method, which is referred to as the Broyden–Fletcher–Goldfarb–Shanno algorithm, by approximating the Hessian matrix of a pure Newton method. The convergence of the proposed gradient algorithm is guaranteed by proposing a line search algorithm. Finally, a performance evaluation shows that the proposed scheme offers a higher sum rate, produces a better outage probability, and achieves a higher multiplexing gain than the existing schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we study a network information flow problem for cellular multiuser two-way relay networks (MU-TWRNs) where uplink and downlink messages are exchanged through a multiantenna relay node using two-way relaying. Both single- and two-cell scenarios are investigated. In particular, for the two-cell scenario, we consider two schemes with and without base station (BS) cooperation, respectively. By comparing the degrees-of-freedom (DOF) upper bounds obtained via cut-set theory, we derive the feasibility conditions to achieve the optimal DOF for all the schemes. These DOF bounds are shown to be achieved by suitably applying some physical-layer signaling techniques, such as physical-layer network coding, signal alignment, block diagonalization, and the newly proposed successive interference nulling. By comparing one-way relaying in terms of the normalized DOF, we observe that the proposed two-way-relaying-based scheme can double the performance with symmetric antenna configurations; however, the gain is reduced under unbalanced antenna configurations. [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, a low-complexity detection scheme is proposed for an underdetermined multiple-input–multiple-output (UD-MIMO) wireless communication system that employs $N$ transmit antennas and M < N$ receive antennas. The proposed scheme combines a simplified parallel interference cancelation (S-PIC) with the block decision feedback equalization (BDFE) algorithm. To account for the extra (N - M)$-dimension in the transmitted signal, the UD-MIMO system is partitioned into two subsystems: one with (N - M)$ transmit antennas and the other one with M sequences in the first subsystem, with $Q$ being the constellation size, the proposed scheme explores only a small number of candidate sequences in the first subsystem; thus, it achieves significant complexity reduction. Two new candidate sequence selection methods are proposed. In the first iteration, the candidate sequences used for PIC are selected by exploring the statistical properties of the received signals. In the second iteration and beyond, the set containing the candidate sequences is constructed by utilizing the soft information generated from the previous iteration. The proposed scheme provides a balanced tradeoff between computational complexity and bit error rate (BER) performance. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a novel low-complexity beamforming algorithm for multiuser successive maximum ratio transmission (MS-MRT) toward space-division multiplexing to achieve video quality maximization in the downlink of a multiuser (MU) multiple-input–multiple-output (MIMO) orthogonal frequency-division multiple-access (OFDMA)-based fourth-generation (4G) wireless network. We compare the performance of this algorithm in terms of system throughput and video quality with the two popular precoding techniques, namely, block diagonalization (BD) and successive optimization (SO). We also compare its performance with the generalized versions of these two algorithms termed coordinated transmit–receive processing (CTR)-BD and CTR-SO algorithms, respectively. Further, we propose an extension of the MS-MRT scheme to broadcast scenarios, termed broadcast successive maximum ratio transmission (BS-MRT), which computes the optimal broadcast beamforming vector to maximize the video quality at each of the broadcast group members while maintaining orthogonality to the previously scheduled user groups. We also demonstrate that the proposed MS-MRT and BS-MRT schemes can be naturally adapted to the context of various MU OFDMA scheduling algorithms such as proportional fairness (PF) and round robin (RR), to name a few, to maximize video quality through optimal scheduling in the presence of a large number of users. We discuss implementations of the proposed MS-MRT scheme in association with these scheduling algorithms for MU unicast and broadcast video transmission scenarios. The simulation results presented in this work rely on the rate models derived using the Joint Scalable Video Model (JSVM) software developed by the Joint Video Team (JVT) and are, thus, readily applicable in practice. The presented results clearly demonstrate the ability of the proposed algorithm to maximize the video quality in comparison with the other competing MU MIMO precoding techniques. Further, employing the proportional fair scheduling algorithm in conjunction with the MS-MRT results in an overall enhancement in the received video quality compared with the RR and max-rate algorithms. [ABSTRACT FROM PUBLISHER]

Recently, a new paradigm for cognitive radio networks has been advocated, where primary users (PUs) recruit secondary users (SUs) to cooperatively relay the primary traffic and in return grant the SUs the right to access the channel. However, all existing studies on such cooperative cognitive radio networks (CCRNs) operate in the temporal domain only, which limits the performance of both PUs and SUs. On the other hand, multiple-input–multiple-output (MIMO) enables transmission of multiple independent data streams in the spatial domain to improve capacity. Taking advantage of the MIMO technique in CCRNs is an unexplored area that we investigate in this paper. We propose a novel MIMO-CCRN framework, which enables the SUs to utilize MIMO techniques to cooperatively relay the traffic for the PUs, while concurrently accessing the same channel to transmit their own traffic. Specifically, we consider two typical network scenarios. For the case of a general PU link and multiple SUs, we provide theoretical analysis for the link rates and then formulate an optimization model based on a Stackelberg game to maximize the utilities of PUs and SUs. In addition, we extend our analysis to a practical cellular network with multiple MIMO-empowered femtocells, and provide an algorithm to find a stable matching of the PUs and SUs. Evaluation results show that high utility gains are achieved by both PUs and SUs by leveraging MIMO spatial cooperation in our proposed framework. [ABSTRACT FROM PUBLISHER]

In this paper, system design for a multiple-input–multiple-output (MIMO) relay broadcast channel with individual signal-to-interference-plus-noise ratio (SINR) constraints at mobile stations (MSs) is considered. By exploring the structure of downlink–uplink duality at either the base station (BS) or the relay station (RS), we propose two schemes of joint power allocation and beamforming design at the BS and the RS. The problem of the existence of feasible solutions under practical power constraints at the BS and the RS with given SINR targets is considered first. Then, the problem of sum power minimization is considered. Each design problem can be efficiently solved using optimal joint power allocation and beamforming under the framework of convex optimization. We also show that with subchannel pairing at the RS, the transmission power can be further reduced. Finally, a generalization to the multihop scenario is provided to further improve power efficiency. [ABSTRACT FROM PUBLISHER]

This paper studies robust interference mitigation against the imperfectness of channel knowledge involved in the interference link of a multiple-input–multiple-output (MIMO) cognitive radio (CR) system that coexists with a primary radio (PR) system via opportunistic spectrum-sharing (OSS) scheme. The robust design leads to a seemingly complicated matrix-valued problem. Nevertheless, we show that it can be equivalently converted into two convex semidefinite programs (SDPs). One of them is identified as a null-forcing approach with closed-form power allocation, and the other can be reduced to a convex scalar power allocation subproblem by properly relaxing the interference constraint. Numerical results demonstrate significant performance gain of the robust design over previous nonrobust strategies. [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]

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]

In this paper, we propose a distributed beamforming scheme to realize a full-duplex relay (FDR) in multiuser multiple-input–multiple-output (MIMO) relaying systems. In the proposed scheme, each mobile and relay station performs distributed transmit beamforming and receive combining, whereas the base station performs ordinary multiuser MIMO transmission. Using the channel reciprocity, the proposed FDR scheme can be realized in an iterative way with no cooperation among nodes. Numerical results show that the proposed scheme provides substantial performance improvement compared with the half-duplex relay. [ABSTRACT FROM PUBLISHER]

This paper considers a multiple-input–multiple-output (MIMO) cognitive radio network, in which a single primary user (PU) coexists with multiple secondary users (SUs). Standard cognitive radio techniques require perfect channel state information (CSI) and are sensitive to the errors in channel estimation. In practice, such errors are inevitable due to finite feedback resources, quantization errors, and other physical constraints. As a result, robustness has become a crucial issue. Under the assumption of norm-bounded channel imperfections, we develop a robust energy-aware design that strives to admit the maximum number of served SUs and enhance the transmit rate of the secondary links while using the least transmit power while imposing the upper limit of the interference temperature to the PU. A utility function is introduced to achieve the multi-objective function by dealing with the tradeoff between maximizing the transmit rate and minimizing the transmit power. Instead of using the deterministic target, the signal-to-interference-and-noise ratio (SINR) target becomes one of the ongoing optimization variables, which is dynamically adapted with the channel condition under the pre-specified bit-error-rate (BER) requirement, and acts as admission control implicitly, i.e., the cognitive link is not allowed to transmit as long as its SINR falls to zero. Due to its nonconvexity and NP-hardness, the underlying problem is reformulated in a semidefinite programming (SDP) form and solved via an iterative bisection search approach. Simulation results are provided to validate the robustness and efficiency of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel matrix decomposition method, called generalized multi-unitary decomposition (GMUD), and use it to achieve robust multi-antenna multi-user multiple-input–multiple-output (MIMO) precoding with limited and partial channel information feedback. GMUD transforms complex matrix {H} into \bf H = \bf P\theta,\, r{\bf R}r{\bf Q}\theta,\, r^{H}, where \bf Rr is a lower triangular matrix, and \bf P\theta,\, r and \bf Q\theta,\, r are unitary matrices. A unique feature of GMUD is that it gives multiple solutions of the unitary matrices \bf P\theta,\, r and \bf Q\theta,\, r based on two parameters, namely the direction parameter \theta and magnitude parameter r. This property enables the GMUD precoder to steer the precoding vectors of different users to jointly optimize their performance. Compared with regularized-inverse precoding (an existing multi-user MIMO precoding technique that we have extended to handle multiple receive antennas), the advantages of GMUD precoding are that it requires only partial channel state information (CSI) from the users, and its performance is robust to CSI quantization. [ABSTRACT FROM PUBLISHER]

The objective of this paper is to study the performance of a multicell vector perturbation (MVP) precoding technique under practical situations in a network multiple-input multiple-output (MIMO) scheme employing joint transmission. The conventional perturbation strategy that minimizes the total power is considered, and the power at each base station (BS) is properly scaled to enforce per-BS power constraints. In our scenario, we consider multiple-antenna users and use block diagonalization (BD) as the linear front-end precoder for VP. The sum rate for the MVP in the case of uniformly distributed input and an asymptotic upper bound on the sum rate at high signal-to-noise ratios (SNRs) are derived. In addition, using the asymptotic upper bound on the individual user rates, we propose a proportionally fair (PF) user scheduling algorithm of lower complexity and better performance compared with the benchmark fair semiorthogonal user selection (SUS) algorithm. As opposed to the PF-SUS, the proposed PF scheduling algorithm requires no predefined correlation threshold. Furthermore, we study the impact of backhaul delay on the performance of both VP and BD by deriving bounds on the sum rate. The numerical results show that MVP in the case of perfect channel state information (CSI) outperforms multicell BD. In the presence of a backhaul delay, the performance of MVP significantly degrades, but the upper bound on the sum rate for MVP is still higher than for multicell BD. [ABSTRACT FROM PUBLISHER]

In downlink multiuser multiple-input–multiple-output (MIMO) systems, block diagonalization (BD) is a practical linear precoding scheme that completely eliminates interuser interference. However, its sum rate performance is rather poor in practical signal-to-noise ratio (SNR) regions due to the transmit power boost problem. In this paper, we propose a modified BD precoding scheme to improve its low-to-medium SNR performance with the so-called “effective SNR enhancement” technique. The proposed transmit covariance matrices are obtained by first solving a power minimization problem subject to the minimum rate constraint achieved by BD and then properly scaling the solution until the power constraint is active. The power minimization problem is nonconvex in general. We therefore propose an efficient algorithm that approximately solves the problem. Simulation results demonstrate significant sum rate gains over BD and existing minimum mean square error (MMSE)-based precoding schemes. [ABSTRACT FROM PUBLISHER]

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]

For next-generation network topologies, the distributed wireless ad-hoc network is one of the most challenging issues because of the inherent node intelligence decision. Nevertheless, due to the randomness of node distribution, it is difficult to achieve high efficiency without signaling to neighboring nodes to coordinate random interference among the nodes, which, in turn, leads to high computational overhead in general. In this paper, we propose a framework of distributed multiple-input–multiple-output (MIMO) ad-hoc networks to improve link capacity while achieving computational simplicity without interworking with other links in a fully distributed manner. To achieve this goal, we align three main resource management algorithms, i.e., the distributed link-scheduling algorithm (DLSA), the distributed power allocation algorithm (DPAA), and the distributed cooperative beamforming algorithm (DCBA). In the simulation results, performance has proven to be promising in terms of the average sum rate, compared with that of other conventional schemes. [ABSTRACT FROM PUBLISHER]

We consider linear precoding in the downlink of a multiuser multiple-input–single-output (MISO) overlay cognitive radio (CR) network, wherein a primary base station (PBS) and a cognitive base station (CBS) share the same frequency band to transmit to a number of primary users (PUs) and secondary users. Conventionally, linear precoding techniques in a CR network aim to limit or completely cancel interference to the PUs while achieving maximum downlink throughput of the CR system. In this paper, we investigate novel adaptive linear precoding techniques at the CBS to exploit the interference to the primary and secondary systems, instead of its cancellation, by exploring the potential of making use of interference energy when the interference between the two systems is mutually constructive on an instantaneous basis. By doing so, the received signal-to-noise ratio (SNR) is enhanced by the signal energy gleaned from the constructive interference. In this direction, constructive-interference-based adaptive linear precoding techniques are proposed for the CR network, assuming a simple zero-forcing precoder at the PBS and noncausal knowledge of the primary message at the CBS. The presented analysis and simulations show that the proposed precoding techniques outperform conventional techniques, as the CR transmission actively enhances the performance of the PUs through constructive interference while achieving significant throughput for its own transmission. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a sequential and incremental precoder design for downlink joint transmission (JT) network multiple-input–multiple-output (MIMO) systems with imperfect backhaul links. The objective of our design is to minimize the maximum of the substream mean square errors, which dominates the average bit error rate (BER) performance of the system. In the proposed scheme, we first optimize the precoder at the serving base station (BS) and then sequentially optimize the precoders of nonserving BSs in the JT set according to the descending order of their probabilities of participating in the JT. The BS-wise sequential optimization process can improve system performance when some BSs have to temporarily quit the JT operations because of poor instant backhaul conditions. In addition, the precoder of an additional BS is derived in an incremental way, i.e., the sequentially optimized precoders of the previous BSs are fixed, and thus, the additional precoder plays an incremental part in multi-BS JT operations. An iterative algorithm is designed to jointly optimize the substream precoder and substream power allocation for each additional BS in the proposed sequential and incremental optimization scheme. Simulations show that, under the practical backhaul link conditions, our scheme significantly outperforms the autonomous global precoding scheme in terms of BER performance. [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 investigates transmit antenna selection for linearly precoded multiuser multiple-input–multiple-output (MU-MIMO) systems. First, in some precoded single-user MIMO systems, using all transmit antennas does not always lead to the best performance due to ill-conditioned channel matrices. This condition motivates us to investigate whether a similar result can be obtained in MU-MIMO systems. Based on the derived analytical results, we found that, for a given number of transmit antennas, decreasing the number of active transmit antennas [number of radio frequency (RF) units] always degrades system performance in the linearly precoded MU-MIMO systems. However, in practical systems, RF units are expensive. To reduce the hardware cost, antenna selection is usually used to reduce the number of RF units. Thus, we further analyze the performance loss due to transmit antenna selection (TAS). These analytical results provide good design references for using TAS in practical systems. Moreover, based on the analytical results, we proposed several simple TAS algorithms for linearly precoded MU-MIMO systems. Complexity analysis and simulation results show that the computational complexity of the proposed algorithms can significantly be reduced, whereas the performance is still comparable with the optimal selection scheme. As a result, the analyzed results enable us to better understand how TAS affects the MU-MIMO systems. In addition, the proposed algorithms make TAS more feasible to be used in practical systems. [ABSTRACT FROM PUBLISHER]

This paper studies the rate maximization problem and designs the beamforming strategy for relay-aided multiuser multiantenna cognitive radio (CR) network that coexists with a primary radio (PR) system via opportunistic spectrum sharing (OSS). The beamforming is characterized by two layers: 1) Cognitive beamforming (CB) is employed by CR base station (BS), CR relay station (RS), and secondary users (SUs) to mitigate the interference to and from the PR. 2) Joint CR-BS and CR-RS beamforming is used to maximize the weighted sum rate of the SUs. Since the optimization turns out to be nonconvex, we apply the classic Blahut-Arimoto algorithm and solve the original problem through an iterative approach. Interestingly, each iterative step involves only convex optimizations whose closed forms can be found. Moreover, we derive an upper bound for the sum rate to assist system analysis. Numerical results show that the proposed approach achieves higher performance, compared with the widely studied diagonally structured beamformer design. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of mode switching in multiple-input–multiple-output (MIMO) broadcast channels utilizing the Per-User Unitary Rate Control (PU2RC) transmission scheme is considered. Since there is no mathematical expression for the achievable rate of the PU2RC systems, it is proposed to approximate them using proper bounds. It is shown that certain simple feedback distributions will lead to tight bounds on the achievable rates of the PU2RC systems. The proposed bounds are used for the calculation of mode-switching points and maximization of the system rate under different multiplexing order conditions. The asymptotic behavior of the preferred modes is also studied under high-signal-to-noise-ratio (SNR) and low-SNR conditions, and it is shown that the single-user transmission mode is the preferred mode for both regimes. [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]

In this paper, we propose new resource allocation schemes with (or without) adaptive modulation for coordinated multipoint (CoMP) with multiuser multiple-input multiple-output orthogonal frequency-division multiple-access (MIMO-OFDMA). In the proposed schemes, a practical linear pre- and postprocessing technique is used to cancel interuser interference and decompose a single-user MIMO channel into parallel noninterfering spatial layers. The transmit power is allocated to spatial layers with (or without) adaptive modulation under the total base station (BS) power constraint and the per-BS power constraint. The set of users for each subcarrier is determined by the exhaustive search user allocation, the sum rate-based user allocation, and the random user allocation. Simulation results show that the proposed schemes enhance the sum rate. [ABSTRACT FROM PUBLISHER]