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We consider the problem of differentiated rate scheduling for the downlink (i.e., multi-antenna broadcast channel), in the sense that the rates required by different users must satisfy certain constraints on their ratios. When full channel state information (CSI) is available at the transmitter and receivers, the problem can be readily solved using dirty paper coding (DPC) and the application of convex optimization techniques on the dual problem which is the multiple access channel (MAC). Since in many practical application full CSI may not be feasible and computational complexity prohibitive when the number of users is large, we focus on other simple schemes that require very little CSI: time-division opportunistic (TO) beamforming where in different time slots (of different lengths) the transmitter performs opportunistic beamforming to .the users requiring the same rate, and weighted opportunistic (WO) beamforming where the random beams are assigned to those users having the largest weighted SINR. For single antenna systems we also look at the capacity-achieving superposition coding (SC) scheme. In all cases, we determine explicit schedules to guarantee the rate constraints and show that, in the limit of large number of users, the throughput loss compared to the unconstrained throughput (sum-rate capacity) tends to zero. We further provide bounds on the rate of convergence of the sum-rates of these schemes to the sum-rate capacity. Finally, we provide simulation results of the performance of different scheduling schemes considered in the paper. [ABSTRACT FROM AUTHOR]

Compressive subspace learning (CSL) with the exploitation of space diversity has found a potential performance improvement for wideband spectrum sensing (WBSS). However, previous works mainly focus on either exploiting antenna auto-correlations or adopting a multiple-input multiple-output (MIMO) channel without considering the spatial correlations, which will degrade their performances. In this paper, we consider a spatially correlated MIMO channel and propose two CSL algorithms (i.e., mCSLSACC and vCSLACC) which exploit antenna cross-correlations, where the mCSLSACC utilizes an antenna averaging temporal decomposition, and the vCSLACC uses a spatial-temporal joint decomposition. For both algorithms, the conditions of statistical covariance matrices (SCMs) without noise corruption are derived. Through establishing the singular value relation of SCMs in statistical sense between the proposed and traditional CSL algorithms, we show the superiority of the proposed CSL algorithms. By further depicting the receiving correlation matrix of MIMO channel with the exponential correlation model, we give important closed-form expressions for the proposed CSL algorithms in terms of the amplification of singular values over traditional CSL algorithms. Such expressions provide a possibility to determine optimal algorithm parameters for high system performances in an analytical way. Simulations validate the correctness of this work and its performance improvement over existing works in terms of WBSS performance. [ABSTRACT FROM AUTHOR]

Channel Inversion, and its Minimum Mean Square Error (MMSE) variation, are low complexity methods for Space Division Multiple Access (SDMA) in Multiple Input Multiple Output Broadcast Channel (MIMO-BC). As the channel matrix deviates from orthogonal, these methods result in a waste of transmit power. This paper proposes a trellis precoding method (across time and space) to improve the power efficiency. Adopting a 4-state trellis shaping method from [1], the complexity of the proposed method, which is entirely at the transmitter side, is equivalent to the search in a trellis with 4N states where N is the number of transmit antennas. Numerical results are presented showing that the achievable gains, which depend on the channel realization, can be significantly higher than the traditional shaping gain which is limited to 1.53dB. [ABSTRACT FROM AUTHOR]

In this paper, we explore reduced-connectivity radio frequency (RF) switching networks for reducing the analog hardware complexity and switching power losses in antenna selection (AS) systems. In particular, we analyze different hardware architectures for implementing the RF switching matrices required in AS designs with a reduced number of RF chains. We explicitly show that fully-flexible switching matrices, which facilitate the selection of any possible subset of antennas and attain the maximum theoretical sum rates of AS, present numerous drawbacks such as the introduction of significant insertion losses, particularly pronounced in massive multiple-input multiple-output (MIMO) systems. Since these disadvantages make fully-flexible switching suboptimal in the energy efficiency sense, we further consider partially-connected switching networks as an alternative switching architecture with reduced hardware complexity, which we characterize in this work. In this context, we also analyze the impact of reduced switching connectivity on the analog hardware and digital signal processing of AS schemes that rely on received signal power information. Overall, the analytical and simulation results shown in this paper demonstrate that partially-connected switching maximizes the energy efficiency of massive MIMO systems for a reduced number of RF chains, while fully-flexible switching offers sub-optimal energy efficiency benefits due to its significant switching power losses. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the quantization and the feedback of downlink spatial covariance matrix for massive multiple-input multiple-output (MIMO) systems with cascaded precoding. Massive MIMO has gained a lot of attention recently because of its ability to significantly improve the network performance. To reduce the overhead of downlink channel estimation and uplink feedback in frequency-division duplex massive MIMO systems, cascaded precoding has been used to convert high-dimensional physical channels into low-dimensional effective channels. For the cascaded precoding, the inner precoder is determined by the downlink spatial covariance matrix, which is unknown in the base station (BS). To address this issue, we propose a spatial spectrum-based approach for the quantization and the feedback of the spatial covariance matrix. In this manner, the BS can obtain partial information on the downlink spatial covariance matrix. Our result shows that the inner precoder based on the proposed approach can be viewed as modulated discrete prolate spheroidal sequences and thus achieves much smaller spatial leakage than the traditional discrete Fourier transform submatrix-based precoding. Practical issues for the application of the proposed approach are also addressed in this paper. [ABSTRACT FROM PUBLISHER]

Multiple-input multiple-output (MIMO) technology equips the transmitters with the multiple antennas. It can combine with energy harvesting (EH) to lift the spectrum efficiency and make use of a greener energy resource. A power grid is added to serve as a supplementary source to regulate the not-so-stable harvested energy supply of the system. Besides the MIMO technology being used, the power allocated to the user provided by both EH and the power grid is subject to the epoch power upper bound constraints. The background of these constraints comes from field requirements, such as avoiding the saturation of power allocated to the user(s), avoiding system-level out-of-band power leakage, and reducing interference with other transmitter(s) due to the non-linearity generated via the transmitting mechanisms to the user(s). The epoch power upper bound constraints make this problem more challenging, with the controllable power grid energy budget and its allocation. This paper applies our recently proposed geometric water-filling with group upper bounded power constraints and recursion machinery to form the proposed algorithm for solving the proposed throughput maximization problem. Our algorithm is precisely defined, and further provides the exact solution via the lower degree polynomial complexity. This point is very suitable for the massive MIMO system. To the best of our knowledge, no prior algorithm has been reported in the open literature to solve the targeted problem in this paper. [ABSTRACT FROM PUBLISHER]

In this paper, we present the error performance analysis of a multiple-input multiple-output (MIMO) physical-layer network coding (PNC) system with two different user-antenna selection (AS) schemes in asymmetric channel conditions. For the first antenna selection scheme (AS1), where the user antenna is selected in order to maximize the overall channel gain between the user and the relay, we give an explicit analytical proof that for binary modulations, the system achieves full diversity order of $\min ({N}_{{A}}, {N}_{{B}}) \times {N}_{{R}}$ in the multiple-access (MA) phase, where $N_{A}, N_{B}$ , and $N_{R}$ denote the number of antennas at user ${A}$ , user ${B}$ , and relay ${R}$ , respectively. We present a detailed investigation of the diversity order for the MIMO-PNC system with AS1 in the MA phase for any modulation order. A tight closed-form upper bound on the average SER is also derived for the special case when ${N}_{{R}} = {1}$ , which is valid for any modulation order. We show that in this case, the system fails to achieve transmit diversity in the MA phase, as the system diversity order drops to 1 irrespective of the number of transmit antennas at the user nodes. Additionally, we propose a Euclidean distance (ED) based user-antenna selection scheme (AS2) that outperforms the first scheme in terms of error performance. Moreover, by deriving upper and lower bounds on the diversity order for the MIMO-PNC system with AS2, we show that this system enjoys both transmit and receive diversity, achieving full diversity order of $\min ({N}_{{A}}, {N}_{{B}}) \times {N}_{{R}}$ in the MA phase for any modulation order. Monte Carlo simulations are provided which confirm the correctness of the derived analytical results. [ABSTRACT FROM AUTHOR]

In this paper, we explore low-complexity transmission in physically-constrained massive multiple-input multiple-output (MIMO) systems by means of channel state information (CSI) relaxation. In particular, we propose a strategy to take advantage of the correlation experienced by the channels of neighbour antennas when deployed in tightly packed antenna arrays. The proposed scheme is based on collecting CSI for only a subset of antennas during the pilot training stage and, subsequently, using averages of the acquired CSI for the remaining closely-spaced antennas. By doing this, the total number of radio frequency (RF) chains, for both CSI acquisition and data transmission, and the baseband signal processing are reduced, hence simplifying the overall system operation. At the same time, this impacts the quality of the channel estimation produced after the CSI acquisition process. To characterize this tradeoff, we explore the impact that the number of antennas with instantaneous CSI has on the performance, signal processing complexity, and energy efficiency of time-division duplex (TDD) systems. The analytical and simulation results presented in this paper show that the application of the proposed strategy in size-constrained antenna arrays is able to significantly enhance the energy efficiency against systems with full CSI availability, while approximately preserving their average performance. [ABSTRACT FROM AUTHOR]

In order to enhance secrecy performance of protecting scenarios, understanding the illegitimate side is crucial. In this paper, from the perspective of the illegitimate side, the security attack from a full-duplex cyber-weapon equipped with massive antenna arrays is considered. To evaluate the behavior of the proposed cyber-weapon, we develop a closed-form, a tight approximation, and asymptotic expressions of the achievable ergodic secrecy rate with taking into consideration imperfect channel estimation at the cyber-weapon. The results show that even under some disadvantage conditions, i.e., imperfect channel estimation and self-interference, the full-duplex massive array cyber-weapon can disable traditional physical layer protecting schemes, i.e., increasing the transmit power and the number of antennas at the legitimate transmitter. In addition, when a transmit power optimization scheme for maximizing the difference between the eavesdropping rate and the legitimate rate is applied at the full-duplex cyber-weapon, the malicious attack is even more dangerous. The results also reveal that when the legitimate side faces an advance adversary, it is essential to prevent important information in the training phases exposing to the illegitimate side. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate secure transmission over the large-scale multiple-antenna wiretap channel with finite alphabet inputs. First, we investigate the case where instantaneous channel state information (CSI) of the eavesdropper is known at the transmitter. We show analytically that a generalized singular value decomposition (GSVD)-based design, which is optimal for Gaussian inputs, may exhibit a severe performance loss for finite alphabet inputs in the high signal-to-noise ratio regime. In light of this, we propose a novel Per-Group-GSVD (PG-GSVD) design, which can effectively compensate the performance loss caused by the GSVD design. More importantly, the computational complexity of the PG-GSVD design is by orders of magnitude lower than that of the existing design for finite alphabet inputs while the resulting performance loss is minimal. Then, we extend the PG-GSVD design to the case where only statistical CSI of the eavesdropper is available at the transmitter. Numerical results indicate that the proposed PG-GSVD design can be efficiently implemented in large-scale multiple-antenna systems and achieves significant performance gains compared with the GSVD design. [ABSTRACT FROM PUBLISHER]

In this paper, we characterize the total degrees of freedom (DoFs) of the full-duplex asymmetric multiple-input multiple- output (MIMO) three-way channel. Each node has a separate-antenna full-duplex MIMO transceiver with a different number of antennas, where each antenna can be configured for either signal transmission or reception. We study this system under two message configurations; the first configuration is when each node has two unicast messages to be delivered to the two other nodes, while the second configuration is when each node has two unicast messages as well as one broadcast message to be delivered to the two other nodes. For each configuration, we first derive upper bounds on the total DoF of the system. Cut-set bounds in conjunction with genie-aided bounds are derived to characterize the achievable total DoF. Afterward, we analytically derive the optimal number of transmit and receive antennas at each node to maximize the total DoF of the system, subject to the total number of antennas at each node. Finally, the achievable schemes for each configuration are constructed. The proposed schemes are mainly based on zero-forcing and null-space transmit beamforming. We show that the derived outer and inner bounds on the total DoF are tight for each message configuration. [ABSTRACT FROM PUBLISHER]

This paper studies full-duplex (FD) cellular networks in which a base station (BS) operated in FD mode with multiple antennas supports multiple uplink and downlink users simultaneously in the same wireless channel. Two typical FD cellular scenarios are considered, one with half-duplex (HD) users and the other with FD users along with the FD BS. For both the cases, a novel constructive method is developed for finding a closed-form interference alignment (IA) solution, named cyclic IA. The core idea behind this approach is to construct a set of loop-equations enabling IA in a cyclic manner, so that beamforming vectors are sequentially determined by solving an eigenvalue problem. It is shown analytically that the proposed cyclic IA can achieve the optimal sum degrees-of-freedom (DoF) when the number of user antennas is large enough to meet the derived conditions. In particular, it is shown that the proposed scheme achieves a twofold DoF gain compared with conventional HD cellular networks even in the presence of inter-link interference, provided the number of users becomes large enough compared with the ratio of the number of BSs and user antennas. Simulation results demonstrate that not only are the analytical DoF results valid, but under a practical multi-cell scenario, the proposed cyclic IA offers significant throughput gains depending on the cell radius. [ABSTRACT FROM PUBLISHER]

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

A massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of terminals. These systems demonstrate large gains in spectral and energy efficiency compared with the conventional MIMO technology. As the number of antennas grows, the performance of a massive MIMO system gets limited by the interference caused by pilot contamination. Ashikhmin and Marzetta proposed (under the name of Pilot Contamination Precoding) large scale fading precoding (LSFP) and large scale fading decoding (LSFD) based on limited cooperation between base stations. They showed that zero-forcing LSFP and LSFD eliminate pilot contamination entirely and lead to an infinite throughput as the number of antennas grows. In this paper, we focus on the uplink and show that even in the case of a finite number of base station antennas, LSFD yields a very large performance gain. In particular, one of our algorithms gives a more than 140 fold increase in the 5% outage data transmission rate! We show that the performance can be improved further by optimizing the transmission powers of the users. Finally, we present decentralized LSFD that requires limited cooperation only between neighboring cells. [ABSTRACT FROM PUBLISHER]

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

In this paper, we consider a wireless-powered communication network in which a multiple-antenna two-way AF relay transfers power to multi-pair of single antenna users. A harvest-then-transmit protocol is adopted where the relay first broadcasts wireless power to all the users during a power transfer phase. Multiple pairs of users then use the harvested energy to exchange information through the relay over two phases: up-link and down-link. In the up-link phase, all the users transmit their independent signals to the relay, whereas in the down-link phase, the relay amplifies and forwards the received signals to the intended users. In order to mitigate the interference, zero-forcing reception and transmission is applied at the relay. To characterize system performance, we consider ergodic spectral and energy efficiencies in three different cases based on the knowledge of the channel state information (CSI) at the relay in the power transfer phase, namely: 1) unknown CSI; 2) partially known CSI; and 3) perfectly known CSI. In light of this, new analytical expressions for the ergodic spectral and energy efficiencies are derived for the three cases and Monte Carlo simulations are provided throughout to validate our analysis. The impacts of some important system parameters, such as energy harvesting time, energy harvesting efficiency, number of user-pairs, and relay antennas, on the adopted performance metrics are investigated. [ABSTRACT FROM PUBLISHER]

This paper studies the behavior of the sum-rate of outdoor multi-user multiple input multiple output systems, where a uniform linear array is utilized at the base station (BS), as the number of BS antennas and the number of users increase. Two schemes are studied for the downlink, the zero-forcing and the maximum ratio transmission (MRT). To begin with, the channel matrix is described deterministically using direct scattering theory. Its matrix elements are the Fourier coefficients of functions that have a physical significance, being connected to the geometry of the environment. For the case when the energy is not arriving at the BS from every spatial direction, we prove for the ZF scheme that the achievable sum-rate behavior is sublinear in the number of antennas at the BS. For the MRT scheme, we prove that there is a link between the sum-rate and the distribution of the users in the city. To numerically evaluate the sum-rate for a given city, schematically described by its streets and its buildings, we introduce a model for the Fourier coefficients of the aforementioned functions, which mixes geometrical and statistical ingredients. We randomly distribute high buildings that will act as strong scatterers and look at the influence of their number on the sum-rate. With the ZF scheme, we perform the calculations for the case where the number of BS antennas, MT , is equal to the number of users, MR, and for the case where MT is larger than MR . We observe that the sum-rate first increases linearly with the number of BS antennas, and becomes sublinear after MT reaches a certain value. The threshold depends on the number of high buildings. With the MRT scheme, the calculations confirm the theoretical predictions, and the sum-rate is greater if the users are spread over all of the city. [ABSTRACT FROM PUBLISHER]

The explosion of mobile data traffic calls for new efficient 5G technologies. Massive multiple-input multiple-output (MIMO), which has shown the great potential in improving the achievable rate with a very large number of antennas, has become a popular candidate. However, the requirement of deploying a large number of antennas at the base station may not be feasible in indoor scenarios due to the high implementation complexity. Does there exist a good alternative that can achieve similar system performance to massive MIMO for indoor environment? In this paper, we show that by using time-reversal (TR) signal processing, with a sufficiently large bandwidth, one can harvest the massive multipaths naturally existing in a rich-scattering environment to form a large number of virtual antennas and achieve the desired massive multipath effect with a single antenna. We answer the above question by analyzing the TR massive multipath effect and the achievable rate with some waveforms. We also derive the corresponding asymptotic achievable rate under a massive multipath setting. Experiment results based on real indoor channel measurements show that the massive multipaths can be revealed with a sufficiently large bandwidth in a practical indoor environment. Moreover, based on our experiments with real indoor measurements, the achievable rate of the TR wideband system is evaluated. [ABSTRACT FROM AUTHOR]

In this paper, we present a comprehensive framework for quadrature spatial modulation (QSM) in generalized fading channels. In particular, the performance analysis of QSM systems in the presence of imperfect channel knowledge and under correlated fading channels is presented. A simple and closed-form expression for the pairwise error probability (PEP) is provided. Based on the obtained PEP, a closed-form upper bound expression for the average bit error probability (BEP) is obtained. The analysis is unified in the sense that it is applicable for any fading channel once its envelope and phase distributions are available. As such, different generalized fading distribution models, namely, $\eta $ – $\mu $ , $\kappa $ – $\mu $ , and $\alpha $ – $\mu $ distributions, are considered. The obtained results clearly show the influence of the fading parameters on the average BEP. In the case of the $\alpha $ – $\mu $ fading channels, increasing $\alpha $ has larger negative impact on the average BEP compared with increasing $\mu $ . For the $\kappa $ – $\mu $ channels, increasing $\mu $ results in increasing the average BEP dramatically when compared with increasing $\kappa $ . In the same context, in $\eta $ – $\mu $ fading channels, as $\mu $ increases the average BEP degrades whereas increasing $\eta $ slightly improves the average BEP. In addition, it is demonstrated that transmit-antenna correlation significantly deteriorate the average BEP when compared with receive-antenna correlation. [ABSTRACT FROM AUTHOR]

Multiuser MIMO (MU-MIMO) in general, and block diagonalization (BD) in particular, are playing a prominent role toward the achievement of higher spectral efficiencies in modern OFDMA-based wireless networks. The utilization of such techniques necessarily has implications in the scheduling and resource allocation processes taking care of assigning subcarriers, power, and transmission modes to the different users. In this paper, a framework for channel- and queue-aware scheduling and resource allocation for BD-based MU-MIMO-OFDMA wireless networks is introduced. In particular, using an SNR-based abstraction of the physical layer, the proposed design is able to cater for different BD-MU-MIMO processing schemes [co-ordinated Tx-Rx (CTR) or receive antenna selection (RAS)], uniform or adaptive power allocation (UPA/APA), continuous or discrete rate allocation (CRA/DRA), and many different scheduling rules. Additionally, the different strategies are complemented by a new greedy user/stream selection algorithm that is shown to perform very close to the optimal user/stream selection policy at a much lower complexity. Results using system parameters typically found in 4G networks reveal that, in most cases, low-complexity solutions (RAS-, UPA-based) achieve a performance close to the one attained by their more complex counterparts (CTR-, APA-based). [ABSTRACT FROM PUBLISHER]

In massive multiple-input multiple-output (MIMO) systems, it may not be power efficient to have a pair of high-resolution analog-to-digital converters (ADCs) for each antenna element. In this paper, a near maximum likelihood (nML) detector for uplink multiuser massive MIMO systems is proposed where each antenna is connected to a pair of one-bit ADCs, i.e., one for each real and imaginary component of the baseband signal. The exhaustive search over all the possible transmitted vectors required in the original maximum likelihood (ML) detection problem is relaxed to formulate an ML estimation problem. Then, the ML estimation problem is converted into a convex optimization problem which can be efficiently solved. Using the solution, the base station can perform simple symbol-by-symbol detection for the transmitted signals from multiple users. To further improve detection performance, we also develop a two-stage nML detector that exploits the structures of both the original ML and the proposed (one-stage) nML detectors. Numerical results show that the proposed nML detectors are efficient enough to simultaneously support multiple uplink users adopting higher-order constellations, e.g., 16 quadrature amplitude modulation. Since our detectors exploit the channel state information as part of the detection, an ML channel estimation technique with one-bit ADCs that shares the same structure with our proposed nML detector is also developed. The proposed detectors and channel estimator provide a complete low power solution for the uplink of a massive MIMO system. [ABSTRACT FROM PUBLISHER]

This paper investigates the performance of the point-to-point multiple-input–multiple-output (MIMO) systems in the presence of a large but finite numbers of antennas at the transmitters and/or receivers. Considering the cases with and without hybrid automatic repeat request (HARQ) feedback, we determine the minimum numbers of the transmit/receive antennas, which are required to satisfy different outage probability constraints. Our results are obtained for different fading conditions and the effect of the power amplifiers efficiency/feedback error probability on the performance of the MIMO–HARQ systems is analyzed. Then, we use some recent results on the achievable rates of finite block-length codes, to analyze the effect of the codewords lengths on the system performance. Moreover, we derive closed-form expressions for the asymptotic performance of the MIMO–HARQ systems when the number of antennas increases. Our analytical and numerical results show that different outage requirements can be satisfied with relatively few transmit/receive antennas. [ABSTRACT FROM PUBLISHER]

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

Secrecy capacity is a fundamental information-theoretic performance metric to predict the maximum data rate of reliable communication, while the intended message is not revealed to the eavesdropper. Motivated by this consideration in this paper, a unified communication-theoretic framework for the analysis of the probability of nonzero secrecy capacity, the secrecy outage probability, and the secrecy capacity of multiple-antenna systems over fading channels is proposed. Specifically, a powerful frequency-domain approach is first developed in which the integrals involved in the evaluation of the probability of nonzero secrecy capacity and secrecy outage probability are transformed into the frequency domain, by employing Parseval’s theorem. A generic approach for the evaluation of the asymptotic secrecy outage probability at high signal-to-noise ratio (SNR) region is also introduced, thus providing useful insight as to the parameters affecting the secrecy performance. Finally, a unified numerical approach for computing the average secrecy capacity of multiple-antenna systems under arbitrary fading environments is developed. The proposed framework is general enough to accommodate any well-known multiantenna transmission technique and fading model. Finally, the secrecy performance of several multiple-antenna system setups is assessed, in the presence of generalized fading conditions and arbitrary antenna correlation, while various numerical and computer simulation results are shown and compared to substantiate the proposed mathematical analysis. [ABSTRACT FROM AUTHOR]

This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under a Gaussian Interference compounded broadcast channel scenario. The basic idea is to split up the role of the transmit beamforming matrix according to the type of interference caused by each base station. It will be shown that, for a network of L base stations, the proposed method would result in achieving (L-1) degrees of freedom per user and convert the multi-cell multi-user MIMO channel into a set of single-cell single-user MIMO channels. Finally, we derive the relationship between all the relevant network elements as N_t=(L-d_s+1)K^\primeN_r+1, where N_t and $N_r$ are the numbers of transmit and receive antennas, respectively, L$ and d_s$ denote the number of cells and the number of data streams transmitted from each base station, and is the number of users per cell defined under the proposed system model. Hence, we show that the proposed scheme makes it possible to implement interference alignment using less antenna resources. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce a new spatial modulation (SM) technique using one or two active antennas and multiple signal constellations. The proposed technique, which we refer to as Enhanced SM or ESM, conveys information bits not only by the index(es) of the active antenna(s), but also by the constellations transmitted from each of them. The main feature of ESM is that it uses a primary signal constellation during the single active antenna periods and some other secondary constellations during the periods with two active transmit antennas. The secondary signal constellations are derived from the primary constellation by means of geometric interpolation in the signal space. We give design examples using two and four transmit antennas and QPSK, 16QAM, and 64QAM as primary modulations. The proposed technique is compared to conventional SM as well as to spatial multiplexing (SMX), and the results indicate that in most cases, ESM provides a substantial performance gain over conventional SM and SMX while reducing the maximum-likelihood (ML) decoder complexity. [ABSTRACT FROM PUBLISHER]

Spatial modulation (SM) is a recently proposed multiple-input multiple-output (MIMO) architecture that exploits the space domain for information transmission. In this paper, SM systems with continuous amplitude-phase modulation (APM) and the corresponding maximum likelihood (ML) active transmit antenna detector are considered. We introduced a method to compute the theoretical transition probability matrix and the mutual information of the ML antenna detector. For SM multiple-input single-output (MISO) system, we derive the error probability and the mutual information of the antenna detector in closed-form. For multiple receive antenna SM system, the union bound of error probability and the lower bound of antenna detection mutual information are proposed. The analytical results are verified by numerical simulation over Rayleigh fading channels. We investigate systems with different number of antennas and APM symbol input distributions to evaluate the performance of SM. The joint APM and antenna detection mutual information of SM systems is compared to the capacity of vertical Bell Labs layered space-time (V-BLAST) spatial multiplexing MIMO scheme. Our research gives achievable transmission rates of SM-MISO/MIMO systems and can be a guideline for suitable application scenarios. [ABSTRACT FROM PUBLISHER]

In this paper, a novel channel estimation (CE) method is proposed for spatial modulation (SM), a unique single-stream multiple-input–multiple-output transmission technique. In SM, there is only one transmit antenna being active at any time instance. While this property completely avoids inter-channel interference, it results in a challenge to estimate the channel information. In conventional CE (CCE) methods for SM, all transmit antennas have to be sequentially activated for sending pilots. Therefore, the time consumed in CE is proportional to the number of transmit antennas, which significantly compromises the throughput. By exploiting channel correlation, the proposed method, named transmission cross CE (TCCE), has the following characteristics: i) the entire channel is estimated by sending pilots through one transmit antenna; ii) it requires no overhead or feedback; and iii) it achieves a low computational complexity at the receiver. In addition, we propose an analytical framework to compute the distribution of the CE errors over time-varying fading channels. The corresponding average bit error probability (ABEP) bound of SM is also derived for the proposed method. Results show that the proposed ABEP bound matches with the simulations very well. When compared with CCE, the new method obtains a signal-to-noise ratio gain of up to 7.5 dB for medium and high correlations between the transmit antennas. Moreover, an adaptive CE technique can be readily implemented for SM via switching between CCE and TCCE. [ABSTRACT FROM AUTHOR]

In this paper, we propose transmit antenna selection with maximal ratio combining (TAS/MRC) in dual-hop decode-and-forward spectrum-sharing relaying networks with the primary user's interference and outdated channel state information (CSI). In this network, a single antenna that maximizes the received SNR is selected at the secondary transmitter, and the MRC is adopted at the secondary receiver. To efficiently evaluate the impact of key parameters on the system performance, we derive the exact analytical expression for the outage probability of the secondary network in a Rayleigh fading channel. Moreover, we present simple asymptotic expressions for the outage probability in a high SNR regime, which reveal practical insights on the achievable diversity order and coding gain. The findings suggest that whether the outdated CSI concerning the secondary transmission links has significant impact on the outage probability of the system depends on the interference power constraint at primary receivers. Specifically, under the proportional interference power constraint, the achievable diversity order is affected by imperfect CSI regarding the secondary transmission links, and the diversity–multiplexing tradeoff is independent of the primary network. However, under the fixed interference power constraint, the error floor is displayed, and the achievable diversity order reduces to zero regardless of the CSI concerning the secondary transmission links. [ABSTRACT FROM AUTHOR]

Modern communications systems use multiple-input multiple-output (MIMO) and high-order QAM constellations for maximizing spectral efficiency. However, as the number of antennas and the order of the constellation grow, the design of efficient and low-complexity MIMO receivers possesses big technical challenges. For example, symbol detection can no longer rely on maximum likelihood detection or sphere-decoding methods, as their complexity increases exponentially with the number of transmitters/receivers. In this paper, we propose a low-complexity high-accuracy MIMO symbol detector based on the Expectation Propagation (EP) algorithm. EP allows approximating iteratively at polynomial-time the posterior distribution of the transmitted symbols. We also show that our EP MIMO detector outperforms classic and state-of-the-art solutions reducing the symbol error rate at a reduced computational complexity. [ABSTRACT FROM PUBLISHER]

We present bounds and a closed-form high-SNR expression for the capacity of multiple-antenna systems affected by Wiener phase noise. Our results are developed for the scenario where a single oscillator drives all the radio-frequency circuitries at each transceiver (common oscillator setup), the input signal is subject to a peak-power constraint, and the channel matrix is deterministic. This scenario is relevant for line-of-sight multiple-antenna microwave backhaul links with sufficiently small antenna spacing at the transceivers. For the 2x 2 multiple-antenna case, for a Wiener phase-noise process with standard deviation equal to 6^°, and at the medium/high SNR values at which microwave backhaul links operate, the upper bound reported in the paper exhibits a 3\dB gap from a lower bound obtained using 64-QAM. Furthermore, in this SNR regime the closed-form high-SNR expression is shown to be accurate. [ABSTRACT FROM PUBLISHER]

In this paper, the trade-off between energy efficiency (EE) and spectral efficiency (SE) is analyzed for both the uplink and downlink of the distributed multiple-input multiple-output (DMIMO) system over the Rayleigh fading channel while considering different types of power consumption models (PCMs). A novel tight closed-form approximation of the DMIMO EE-SE trade-off is presented and a detailed analysis is provided for the scenario with practical antenna configurations. Furthermore, generic and accurate low and high-SE approximations of this trade-off are derived for any number of radio access units (RAUs) in both the uplink and downlink channels. Our expressions have been utilized for assessing both the EE gain of DMIMO over co-located MIMO (CMIMO) and the incremental EE gain of DMIMO in the downlink channel. Our results reveal that DMIMO is more energy efficient than CMIMO for cell edge users in both the idealistic and realistic PCMs; whereas in terms of the incremental EE gain, connecting the user terminal to only one RAU is the most energy efficient approach when a realistic PCM is considered. [ABSTRACT FROM AUTHOR]

In this paper, we study space-time block code (STBC) designs for two-user MIMO X channels to achieve full diversity when the inter-user interference is cancelled by the group zero-forcing receiver. To do so, we first propose a design criterion and then propose a systematic design to satisfy the criterion so that it achieves full diversity. The code rate approaches one when encoding length gets large. We prove that full diversity can be achieved by the proposed STBC without the channel information at the transmitters. Simulation results are provided to demonstrate the theory. [ABSTRACT FROM AUTHOR]

Opportunistic resource allocation for multiple users utilizing multiple-input multiple-output (MIMO) channel in orthogonal frequency division multiple access (OFDMA) is used to attain the spectral efficiency required in future wireless communications networks. In this paper, we express analytical outage capacity results and average capacity results with optimal rate adaptation for MIMO-OFDMA systems with limited feedback. A resource block (RB)-wise SNR quantization feedback scheme and a best-M feedback method are studied for RB allocation. Feedback based transmit antenna selection (AS) is considered in the analysis. An imperfect feedback channel has a significant impact on the performance of practical feedback based communication. The proposed analysis also considers imperfect feedback in the RB allocation and AS. [ABSTRACT FROM PUBLISHER]

Large-scale propagation effect plays an important role in multiple-input multiple-output (MIMO) relay systems. In particular, the position of the relay (between the source and destination) determines the path-loss effects of adjacent hops, which will further affect the performance of each hop and thus the relay system. In this paper, by minimizing the outage probability of a decode-and-forward (DF) MIMO relay system with orthogonal space-time block coding, we show that relay position optimization improves the finite-SNR (signal-to-noise ratio) diversity gain of a relay system whose adjacent hops have different diversity orders (unbalanced system). Specifically, with relay position optimization, the diversity gain is no longer bounded by that of the weaker hop, i.e., the hop with a lower diversity order, but approaches the diversity order of the stronger hop. This diversity improvement provides a dramatic improvement for the end-to-end outage probability. It will also be shown that although power allocation has no effects on the achievable diversity order, it provides some SNR gains. [ABSTRACT FROM AUTHOR]

This paper proposes a low complexity protocol that preserves full diversity in multiuser amplify-and-forward relay networks with NS antennas at the source, NR antennas at the relay, and ND antennas at each of the K destinations. In the proposed protocol, a two-fold diversity is guaranteed: 1) multi-antenna diversity via transmit antenna selection with maximal-ratio combining (TAS/MRC), and 2) multiuser diversity via opportunistic scheduling. Under perfect feedback with precise channel state information (CSI), we derive new exact and asymptotic symbol error rate (SER) expressions in closed-form for the general case of Nakagami-m fading. We prove that the full diversity order of NSNDKmX+ min{NSNRmY,NRNDKmZ} is guaranteed, where mX, mY, and mZ denote the fading parameters of the source-destination, source-relay, and relay-destination links, respectively. To examine the impact of delayed feedback, we next derive new exact and asymptotic SER expressions in closed-form. We prove that in the presence of delayed feedback, outdated CSI degrades the diversity order to NDmX+ min{NRmY,NDmZ}. In addition, based on our asymptotic expressions, we determine the optimal power allocation between the source and the relay such that the SER is minimized. We show that optimal power allocation offers superior performance over uniform power allocation; highlighting a pivotal design choice for maximizing network performance without investing additional resources. [ABSTRACT FROM AUTHOR]

In this paper, we consider a secrecy relaying communication scenario where all nodes are equipped with multiple antennas. An eavesdropper has the access to the global channel state information (CSI), and all the other nodes only know the CSI not associated with the eavesdropper. A new secrecy transmission protocol is proposed, where the concept of interference alignment is combined with cooperative jamming to ensure that artificial noise from transmitters can be aligned at the destination, but not at the eavesdropper due to the randomness of wireless channels. Analytical results, such as ergodic secrecy rate and outage probability, are developed, from which more insightful understanding of the proposed protocol, such as multiplexing and diversity gains, can be obtained. A few special cases, where outage probability cannot be decreased to zero regardless of SNR, are also discussed. Simulation results are provided to demonstrate the performance of the proposed secrecy transmission protocol. [ABSTRACT FROM AUTHOR]

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLS of the precoder using large-system analysis. We show that the RCI precoder with αLS outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLS and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas. [ABSTRACT FROM AUTHOR]

This paper considers linear precoder optimization problems for multiple-input multiple-output (MIMO) systems. In addition to the conventionally used sum-power constraint, maximum eigenvalue constraint on the precoding matrix is also considered so as to account for power limitations imposed on each antenna by the linearity of its own power amplifier in practical implementations. A framework employing directional derivative is developed to obtain optimal precoder designs for different criteria including maximizing the information rate and minimizing the sum of mean-square error (MSE). It turns out that power allocations in such situations are piecewise linear in sum-power space. The piecewise linear property allows us to generate the entire path of solution through finding out a finite number of breakpoints. A Homotopy-type algorithm is then proposed to obtain the solution for an arbitrary sum-power constraint. The number of breakpoints to be determined in our exact piecewise linear solution is in fact only about two times of the number of transmit antennas, so that our method is super fast and outperforms existing approximate solutions in the literature in both effectiveness and efficiency. Simulated experiments are performed to verify our theoretical analysis. [ABSTRACT FROM AUTHOR]

A novel user relaying scheme based on bit concatenation is proposed for multiple-input multiple-output (MIMO) broadcast channels. In a broadcasting phase, a part of information for a destination user is concatenated to data for a relaying user and transmitted to the relaying user. The destination user receives the part of information via the relaying user in a relaying phase in addition to the data in the broadcasting phase. An achievable rate region for the proposed scheme is derived and an algorithm to characterize the boundary of the rate region is proposed. Our analysis shows that the proposed user relaying in a MIMO BC expands the achievable rate region for the zero-forcing dirty paper coding (ZF-DPC) in the MIMO BC without relaying. It is also shown that the proposed user relaying scheme always outperforms a superposition coding (SC) based user relaying scheme. Optimal and suboptimal user pair scheduling algorithms are investigated for a two-user MIMO BC and the proposed suboptimal user pair scheduling scheme is shown to approach the optimal scheduling when the relaying channel gain is large. [ABSTRACT FROM AUTHOR]

In a MIMO layered architecture, several codewords are transmitted from a multiplicity of antennas. Although the spectral efficiency is maximized if the rates of these codewords are separately controlled, the feedback rate within the link adaptation loop is reduced if they are constrained to be identical. This poses a direct tradeoff between performance and feedback overhead. This paper provides analytical expressions that quantify the difference in spectral efficiency between both approaches for arbitrary numbers of antennas. Specifically, the characterization takes place in the realm of the low- and high-power regimes via expansions that are shown to have a wide range of validity. In addition, the possibility of adjusting the transmit power of each codeword individually is considered as an alternative to the separate control of their rates. Power allocation, however, turns out to be inferior to rate control within the context of this problem. [ABSTRACT FROM AUTHOR]

With mean or covariance channel feedback, the input covariance matrix can be designed to achieve the ergodic capacity of a MIMO fading channel. It is known that the eigenvectors of the optimal input covariance matrix are the same as the eigen-vectors of the channel mean or covariance matrix. However, the optimal power allocation across the elgen-vectors is much less understood. In this paper, two scenarios are investigated: 1) Rician MIMO channels with mean channel feedback, and 2) Rayleigh MIMO channels with covariance channel feedback. We first derive a suboptimal power allocation algorithms in the spatial domain for expected mutual information maximization for two transmit antennas systems, based on an upper bound for the ergodic capacity of a MIMO channel with either channel mean or covariance information at the transmitter. Then, we extend heuristically the results to systems with multiple antennas at both the transmitter and receiver side. The proposed power allocation solution permits a closed-form expression and has a water-filling interpretation. Simulation results reveal that the proposed method performs nearly the same as the optimal solution (which requires highly complex optimization routines over random processes) with inappreciable difference. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the effect of spatial correlation on throughput performance of downlink multi-antenna transmission schemes exploiting multiuser diversity, in which partial channel information such as signal-to-interference plus noise power ratio (SINR) is available at the transmitter. The asymptotic analysis is performed based on the extreme value theory. From this analysis, we demonstrate that the throughput optimal transmission scheme depends on the degree of the antenna correlation and the operating SNR. Especially, the multiuser spatial multiplexing known as the asymptotically optimal transmission scheme is no longer optimal in highly correlated multiple antenna channels. [ABSTRACT FROM AUTHOR]

Multiuser MIMO (MU-MIMO) systems have advantages over single-user MIMO systems in terms of system performance. In MU-MIMO systems, inter-user interference needs to be dealt with especially when linear processing is used. The block diagonalization (BD) method is one of techniques that are widely used to eliminate the inter-user interference. In a cellular system where there are many users, the subset of users which maximizes the system performance should be selected since the base station cannot support all the users in the cell. In this paper, we propose a low complexity MU-MIMO scheduling scheme using BD with chordal distance. For a large number of users, the optimal scheduling technique needs an exhaustive search, which is impractical. One of the key ideas of this paper is to use chordal distance as a measure of orthogonality between different users. Simulation results show the proposed algorithm has throughput close to the optimal scheduling scheme with lower complexity than existing low complexity scheduling algorithms. [ABSTRACT FROM AUTHOR]

This paper provides a systematic characterization of Zero-Forcing (ZF) detectors over multiple-input multiple-output (MIMO) channels that experience both small and large-scale fading. In particular, we consider the generic K distribution (Rayleigh/gamma distribution) to model the composite fading fluctuations and also assume the general case of semi-correlated small-scale fading. In the following, novel exact analytical expressions for the achievable sum rate are derived, followed by asymptotic expressions in the high and low Signal-to-Noise ratio (SNR) regimes. In these limiting cases, two common and insightful affine expansions are studied followed by new, closed-form upper and lower bounds on the sum rate that remain tight for all SNRs. In the second part of the paper, we present exact tractable expressions along with first-order expansions for the symbol error rate (SER) and outage probability; we also quantify the performance of ZF detectors in terms of diversity order and array (or coding) gain. The implications of the model parameters on the ZF detector performance are investigated via Monte-Carlo simulations which also validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

Layered space time processing in spatial multiplexing systems requires the number of receive antennas to be equal to or larger than the number of transmit antennas. However, it is impractical for small-sized mobile units to accommodate a large number of antennas. To loosen this stringent requirement, a novel concept of virtual receive antennas (VRA) for overloaded MIMO system is presented. The VRA system architecture consists of two major parts: fractional timing offset in the transmitter and oversampling at the receive matched filter. This procedure expands the received signal dimension and thus creates virtual receive antennas. Due to these created virtual receive antennas, the minimum number of physical receive antennas could be reduced. In order to explore the potential of VRA, this paper evaluates its system capacity and performance bound. Results show that the VRA system can achieve higher ergodic capacity and outage rate than conventional overloaded MIMO system. Performance analysis also suggests a potential performance gain for the VRA system. To eliminate the created inter-symbol interference in the VRA, time domain and frequency domain equalization are utilized and evaluated. [ABSTRACT FROM PUBLISHER]

The statistical properties of Wishart matrices have been extensively used to analyze the performance of multiple-input multiple-output (MIMO) systems. In particular, the signal-to-noise ratio (SNR) output statistics of several MIMO systems depends on the diagonal distribution of a complex Wishart matrix. In this paper, we derive the joint density of the diagonal elements of a complex Wishart matrix, which follows a multivariate chi-square distribution. The density expression is in the form of an infinite series representation which converges rapidly and is easy to compute. This expression is used to obtain the distribution of the maximum of the diagonal elements, which allows analyzing the performance of two different MIMO systems under practical conditions. First, our statistical results are applied to the outage probability characterization of MIMO systems with receive antenna selection in spatially correlated Rayleigh fading. Then, the same results are used to analyze the outage probability of transmit beamforming systems under limited-rate feedback. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a general framework to quantify the average error probability of the minimum mean squared error based precoding schemes in amplify-and-forward relay networks where all nodes are equipped with multiple antennas. Especially, we investigate spatial multiplexing schemes which transmit multiple data streams simultaneously. Due to difficulty in finding an exact expression of the average error rate, we exploit the high signal-to-noise-ratio (SNR) based approach which allows a simple and accurate characterization of the performance. Then, we derive new closed form expressions for bit error rate performance of both the optimal source-relay joint precoding schemes and the optimal relay only precoding schemes in terms of a coding gain as well as a diversity gain. Taking a different pathloss in each hop into consideration, we evaluate the performance in a generalized environment. Through our analysis, we discuss several interesting observations and provide a helpful guideline for designing MMSE-based relaying systems. Monte-Carlo simulations show that our analytical work accurately predicts numerical results. [ABSTRACT FROM PUBLISHER]

In this paper, we address the issue of multiaccess communication through multi-hop linear non-regenerative relays, where all users, all relay nodes, and the destination node may have multiple antennas. Using a linear minimal mean-squared error (MMSE) receiver at the destination node, we demonstrate that the optimal amplifying matrix at each relay node can be viewed as a linear MMSE filter concatenated with another linear filter. As a consequence, the MSE matrix of the signal waveform estimation at the destination node is decomposed into the sum of the MSE matrices at all relay nodes. We show that at a high signal-to-noise ratio (SNR) environment, this MSE matrix decomposition significantly simplifies the solution to the problem of optimizing the source precoding matrices and relay amplifying matrices. Simulation results show that even at the low to medium SNR range, the simplified optimization algorithms have only a marginal performance degradation but a greatly reduced computational complexity and signalling overhead compared with the existing optimal iterative algorithm, and thus are of great interest for practical relay systems. [ABSTRACT FROM AUTHOR]

In this paper we first analyze some mathematical properties of ergodic capacity and outage capacity functions of the layers in Bell labs layered space-time (BLAST) architectures employing successive decoding and interference cancellation. We then present statistical rate allocation and power allocation methods that optimize the asymptotic performance of BLAST architectures. Since the methods are developed by using ergodic capacity and outage capacity functions of the layers, the allocated rates and powers depend only on a given channel statistic. Finally, we prove that the rate allocation yields a better asymptotic performance than the power allocation. Numerical results show that BLAST architectures with the rate and power allocation perform better by 4 dB and 3 dB, respectively, than a BLAST architecture with the same rate and power in all layers. [ABSTRACT FROM PUBLISHER]