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The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid wireless communication systems have recently received much attention from academia and industry. Most papers make theoretical studies based on elementary models, while the prototyping of RIS-aided wireless communication and real-world field trials are scarce. In this paper, we describe a new RIS prototype consisting of 1100 controllable elements working at 5.8 GHz band. We propose an efficient algorithm for configuring the RIS over the air by exploiting the geometrical array properties and a practical receiver-RIS feedback link. In our indoor test, where the transmitter and receiver are separated by a 30 cm thick concrete wall, our RIS prototype provides a 26 dB power gain compared to the baseline case where the RIS is replaced by a copper plate. A 27 dB power gain was observed in the short-distance outdoor measurement. We also carried out long-distance measurements and successfully transmitted a 32 Mbps data stream over 500 m. A 1080p video was live-streamed and it only played smoothly when the RIS was utilized. The power consumption of the RIS is around 1 W. Our paper is vivid proof that the RIS is a very promising technology for future wireless communications. [ABSTRACT FROM AUTHOR]

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS. [ABSTRACT FROM AUTHOR]

Due to their ability to create favorable line-of-sight (LoS) propagation environments, intelligent reflecting surfaces (IRSs) are regarded as promising enablers for future millimeter-wave (mm-wave) wireless communication. In this paper, we investigate channel estimation for IRS-assisted mm-wave multiple-input multiple-output (MIMO) wireless systems. By leveraging the sparsity of mm-wave channels in the angular domain, we formulate the channel estimation problem as an $\ell _{1}$ -norm regularized optimization problem with fixed-rank constraints. To tackle the non-convexity of the formulated problem, an efficient algorithm is proposed by capitalizing on alternating minimization and manifold optimization (MO), which yields a locally optimal solution. To further reduce the computational complexity of the estimation algorithm, we propose a compressive sensing- (CS-) based channel estimation approach. In particular, a three-stage estimation protocol is put forward where the subproblem in each stage can be solved via low-complexity CS methods. Furthermore, based on the acquired channel state information (CSI) of the cascaded channel, we design a passive beamforming algorithm for maximization of the spectral efficiency. Simulation results reveal that the proposed MO-based estimation (MO-EST) and beamforming algorithms significantly outperform two benchmark schemes while the CS-based estimation (CS-EST) algorithm strikes a balance between performance and complexity. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) consisting of a large number of programmable near-passive units has been a hot topic in wireless communications due to its capability in providing smart radio environments to enhance the communication performance. However, the existing research are mainly based on simplistic channel models, which will, in principle, lead to inaccurate analysis of the system performance. In this paper, we propose a general three-dimensional (3D) wideband non-stationary end-to-end channel model for RIS assisted multiple-input multiple-output (MIMO) communications, which takes into account the physical properties of RIS, such as unit numbers, unit sizes, array orientations and array configurations. By modeling the RIS by a virtual cluster, we describe the end-to-end channel by a superposition of virtual line-of-sight (V-LoS), single-bounced non-LoS (SB-NLoS), and double-bounced NLoS (DB-NLoS) components. We also derive an equivalent cascaded channel model and show the equivalence between end-to-end and cascaded modeling of RIS channels. Then, a sub-optimal solution with low complexity is used to derive the RIS reflection phases. The impact of physical properties of RIS, such as unit numbers, unit sizes, array orientations, array configurations and array relative locations, on channel statistical characteristics has been investigated and analyzed, the results demonstrate that the proposed model is helpful for characterizing the RIS-assisted communication channels. [ABSTRACT FROM AUTHOR]

The universal filtered multicarrier (UFMC) modulation is among the most considered solutions for the realization of beyond orthogonal frequency division multiplexing (OFDM) air interfaces for future wireless networks. This paper focuses on the design and analysis of a UFMC transceiver equipped with multiple antennas and operating at millimeter-wave carrier frequencies. This paper provides the full mathematical model of an MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission and for the case of multiple-packet continuous transmission. In the latter situation, this paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, several considered detection structures and transmission schemes are compared in terms of bit-error rate, root-mean-square error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear minimum mean-square error (MMSE) data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10%–13%. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance. [ABSTRACT FROM AUTHOR]

This paper addresses point-to-point communication over block-fading channels with independent fading blocks. When both channel state information at the transmitter and receiver (CSIR) are available, most achievable schemes use separable coding, i.e., coding independently and in parallel over different fading states. Unfortunately, separable coding has drawbacks, including large memory requirements at both communication ends. In this paper, a lattice coding and decoding scheme is proposed that achieves the ergodic capacity without separable coding, with lattice codebooks and decoding decision regions that are universal across channel realizations. We first demonstrate this result for fading distributions with discrete, finite support whose sequences are robustly typical. Results are then extended to continuous fading distributions, as well as multiple-input multiple-output (MIMO) systems. In addition, a variant of the proposed scheme is presented for the MIMO ergodic fading channel with CSIR only, where we prove the existence of a universal codebook that achieves rates within a constant gap to capacity for finite-support fading distributions. The gap is small compared with other schemes in the literature. Extension to continuous-valued fading is also provided. [ABSTRACT FROM AUTHOR]

The integration of local device-to-device (D2D) communications and cellular connections has been intensively studied to satisfy co-existing D2D and cellular communication demand. In future cellular networks, there will be numerous standby users possessing D2D communication capabilities in close proximity to each other. Considering that these standby users do not necessarily request D2D communications all the time, in this paper we propose a hybrid D2D-cellular scheme to make use of these standby users and to improve the rate performance for cellular users. More specifically, through D2D links, a virtual antenna array can be formed by sharing antennas across different terminals to realize the diversity gain of MIMO channels. This paper considers the use of millimeter wave links to enable high data rate D2D communications. We then design an orthogonal D2D multiple access protocol and formulate the optimization problem of joint cellular and D2D resource allocation for downlink transmissions using the proposed scheme. We obtain a closed-form solution for D2D resource allocation, which reveals useful insights for practical system design. Numerical results from extensive system-level simulations demonstrate that the rate performance of cellular users is significantly improved. [ABSTRACT FROM AUTHOR]

In this paper, we study the capacity and symbol error probability (SEP) of generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) using measured channels that are obtained by channel sounding in an indoor office environment at 60GHz. Spatial modulation (SM) and GSM are emerging low-complexity MIMO schemes that have been extensively researched for low-GHz (below 6GHz) communications. Recently, they have been considered and shown to be promising also for (mmWave) communications. In the simplest possible case, they require only one RF chain both at the transmitter (TX) and receiver (RX), and thus, are especially attractive for mmWave communications, in which the number of RF chains needs to be as low as possible. Despite of some early works on the theoretical analysis of SM/GSM for mmWave communications, there have been no investigations using real-world channel data. We focus on the office line-of-sight (LOS) scenario and investigate three problems: 1) the performance of GSM using the extracted LOS component of measured channels; 2) the impact of non-LOS NLOS components on the performance of GSM; and 3) possible simple modulation and reception algorithms for GSM that rely only on the LOS component of the channel. The results being reported in this paper not only validate the main claims of previous studies based on ideal pure LOS channels, but also lead to novel findings. One major conclusion is that NLOS components are harmful to the SEP of GSM and should be avoided. As another important outcome, our results strongly motivate the use of precoding in GSM systems to simultaneously improve the channel capacity and reduce the physical size of MIMO arrays (thus eliminating one major issue of LOS GSM). [ABSTRACT FROM AUTHOR]

It is known that superposition signaling in Gaussian interference networks is capable of improving the achievable rate region. However, the problem of maximizing the rate gain offered by superposition signaling is computationally prohibitive, even in the simplest case of two-user single-input single-output interference networks. This paper examines superposition signaling for the general multiple-input multiple-output broadcast Gaussian interference networks. The problem of maximizing either the sum rate or the minimal user’s rate under superposition signaling and dirty paper coding is solved by a computationally efficient path-following procedure, which requires only a convex quadratic program for each iteration but ensures convergence at least to a locally optimal solution. Numerical results demonstrate the substantial performance advantage of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper investigates nonlinear transceiver design for full-duplex multiple-input multiple-output (FD-MIMO) relay systems. A dual-hop amplify-and-forward relaying protocol is considered. At the destination, nonlinear successive-interference-cancellation (SIC) is used for signal detection. The goal is to find the source and relay precoders such that the symbol-vector error rate (SVER) can be minimized. Due to the loop interference (LI), optimizing the relay precoder in FD systems is much more involved. In this paper, we propose novel designs to solve this problem. Starting from the QR-SIC receiver, we theoretically show that the relay precoder can be solved with a closed-form expression even when the system incurs LI. Then, we consider the system with a minimum mean-squared-error SIC receiver, where the relay precoder design entails a different problem formulation and introduces new challenges. We propose a novel iterative method, with closed-form solutions in each iteration, to solve this problem. Simulations show that our designs can significantly improve the SVER performance for FD-MIMO relay systems. [ABSTRACT FROM AUTHOR]

Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system’s secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup. [ABSTRACT FROM AUTHOR]

In this paper, imperfect feedback-based linear precoding schemes are proposed for multiple-input-multiple-output (MIMO) wireless communication systems, where input symbol streams are encoded by using generalized-orthogonal space-time block codes. The imperfect feedback information drastically degrades the system performance. Therefore, to overcome the effect of erroneous feedback information, error-tolerant weighting (ETW) schemes are implemented by employing diagonal precoder. The communication links are assumed to be Nakagami- $m$ distributed for accurately characterizing practical wireless channels under different fading scenarios. Exact and asymptotic symbol-error-rate (SER) expressions of the considered MIMO system are derived under imperfect feedback with the help of order statistics. The most appropriate values of the transmit weights of the precoder matrix are obtained by minimizing the derived average SER over fixed and adaptive signal-to-noise ratio. Further, we study the trade-off between the proposed optimal and suboptimal feedback-based precoding schemes. Moreover, the ergodic-rate of the ETW schemes is also derived with imperfect feedback for arbitrary MIMO system by using the moment generating function approach. The simulated and analytical results show that a significant performance gain is achieved by the ETW schemes as compared to the uniform power allocation and existing precoding techniques under erroneous feedback information. [ABSTRACT FROM AUTHOR]

Multi-channel (MC) optical wireless communication (OWC) systems employing wave-division multiplexing for outdoors free-space optical communications, or multi-user time-division multiple access for indoors visible-light communications, e.g., can be modeled as parallel channels. Multi-input multi-output OWC systems can also be transformed, possibly with some performance loss, to parallel channels using pre-/post-coding. Studying the performance of such MC-OWC systems requires characterizing the capacity of the underlying parallel channels. In this paper, upper and lower bounds on the capacity of constant parallel OWC channels with a total average intensity constraint are derived. Then, this paper focuses on finding intensity allocations that maximize the lower bounds given channel-state information at the transmitter (CSIT). Due to its nonconvexity, the Karush–Kuhn–Tucker conditions are used to describe a list of candidate allocations. Instead searching exhaustively for the best solution, low-complexity near-optimal algorithms are proposed. The resulting optimized lower bound nearly coincides with capacity at high signal-to-noise ratio (SNR). Under a quasi-static channel model and in the absence of CSIT, outage probability upper and lower bounds are derived. Those bounds also meet at high SNR, thus characterizing the outage capacity in this regime. Finally, the results are extended to a system with both average and peak intensity constraints. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a combined full duplex (FD)- and half duplex (HD)-based transmission and channel acquisition model for an open-loop multiuser multiple-input multiple-output (MIMO) systems. Assuming residual self-interference at the base station (BS), the idea is to utilize the FD mode during the uplink (UL) training phase in order to achieve simultaneous downlink (DL) data transmission and UL CSI acquisition. More specifically, the BS begins serving a user when its CSI becomes available, while at the same time, it also receives UL pilots from the next scheduled user. We investigate both zero-forcing (ZF) and maximum ratio transmission MIMO beamforming techniques for the DL data transmission in the FD mode. The BS switches to the HD mode once it receives the CSI of all users and it employs ZF beamforming for the DL data transmission until the end of the transmission frame. Furthermore, we derive closed-form approximations for the lower bounded ergodic achievable rate relying on the proposed model. Our numerical results show that the proposed FD–HD transmission and channel acquisition approach outperforms its conventional HD counterpart and achieves higher data rates. [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 this paper, we consider massive multiple input multiple output systems that employ linear precoding techniques and are impaired by transmitter-side nonlinearities and channel estimation errors. We present an analytical method for the statistical characterization of the transmitted signals and develop a general framework to obtain analytically, the performance of different precoding techniques under the assumption of imperfect channel state information and for different types of nonlinearities. Regardless of the particular nonlinear transmission scenario, it is shown that the performance penalty associated to the nonlinear distortion can be tolerable if the number of transmit antennas is greater than the number of independent data streams. [ABSTRACT FROM AUTHOR]

To achieve spectral-efficient massive access in future wireless networks, this paper proposes a comprehensive fully non-orthogonal communication framework. First, we design a fully non-orthogonal communication scheme which consists of non-orthogonal channel estimation and non-orthogonal multiple access. Then, we analyze the performance of the proposed fully non-orthogonal communication, and derive a tight lower bound on the spectral efficiency in terms of key system parameters and channel conditions. Meanwhile, several novel insights are provided on spectral efficiency via asymptotic analysis in three important cases, i.e., a large number of base station (BS) antennas, a high BS transmit power, and perfect channel state information (CSI) at the BS. Finally, we optimize the performance of the proposed fully non-orthogonal communication and present two simple but efficient optimization algorithms for maximizing the weighted sum of spectral efficiency. Extensive simulation results validate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

This paper presents exact, novel formulations for the probability density function and cumulative distribution function for the product of two independent and non-identically distributed $\alpha $ - $\mu $ , $\kappa $ - $\mu $ , and $\eta $ - $\mu $ variates. The expressions are given in terms of both 1) generalized Fox H-function and 2) easily computable series expansions. The formulations derived can be directly used to explore the performance of a number of wireless communication processes, including multihop systems, cascaded channels, radar communications, multiple-input multiple-output links, and others. Due to the high flexibility of the above-mentioned distributions, the results presented here comprise a substantial number of useful product distributions. As application examples, performance metrics for the cascaded fading channel are derived. The validity of the expressions is confirmed via Monte Carlo simulation. It is noteworthy that, because any composite multipath-shadowing fading model is obtained as a particular case of the product of two fading variables, the results given here provide a plethora of composite multipath-shadowing fading scenarios. [ABSTRACT FROM PUBLISHER]

This paper investigates secure cooperative transmissions in a dual-hop MIMO relay system using a combined transmit antenna selection (TAS) and maximal-ratio combining (MRC) scheme over the Nakagami- $m$ fading channels, where an adaptive decode-and-forward relaying protocol and an multi-antenna eavesdropper are considered. Due to the feedback delay, channel state information (CSI) for TAS might be outdated at both the source and the relay. To evaluate the secrecy performance of the TAS/MRC scheme and the impacts of outdated CSI, the closed-form expressions for the metrics of exact ergodic secrecy rate and exact secrecy outage probability are derived under both perfect and outdated CSI conditions in a channel feedback error model. In order to explicitly reveal the behaviors of the secrecy performance in high signal-to-noise ratio regime, asymptotic expressions for both the metrics are further derived. As validated by simulation results, analytically numerical results demonstrate that outdated the CSI always results in a loss in the secrecy performance, but the loss can be recovered by increasing the number of antennas at legitimate receivers. Furthermore, the outdated CSI yields a reduced secrecy diversity order, whereas only the perfect CSI leads to the full secrecy diversity order. [ABSTRACT FROM PUBLISHER]

Ultra-dense cloud radio access networks (C-RANs) are an example of the architectures that will be critical components of the next-generation wireless systems. In a C-RAN architecture, an amorphous cellular framework, where each user connects to a few nearby remote radio heads (RRHs) to form its own cell, appears to be promising. In this paper, we study the ergodic capacity of such amorphous cellular networks at high signal-to-noise ratios (SNRs) where we model the distribution of the RRHs by a Poisson point process. We derive tractable approximations of the ergodic capacity at high-SNRs for arbitrary antenna configurations, and tight lower bounds for the ergodic capacity when the numbers of antennas are the same at both ends of the link. In contrast to prior works on distributed antenna systems, our results are derived based on random matrix theory and involve only standard functions which can be much more easier evaluated. The impact of the system parameters on the ergodic capacity is investigated. By leveraging our analytical results, we propose two efficient scheduling algorithms for RRH selection for energy-efficient transmission. Our algorithms offer a substantial improvement in energy efficiency compared with the strategy of connecting a fixed number of RRHs to each user. [ABSTRACT FROM AUTHOR]

The non-regenerative massive multi-input-multi-output (MIMO) non-orthogonal multiple access (NOMA) relay systems are introduced in this paper. The NOMA is invoked with a superposition coding technique at the transmitter and successive interference cancellation (SIC) technique at the receiver. In addition, a maximum mean square error-SIC receiver design is adopted. With the aid of deterministic equivalent and matrix analysis tools, a closed-form expression of the signal to interference plus noise ratio (SINR) is derived. To characterize the performance of the considered systems, closed-form expressions of the capacity and sum rate are further obtained based on the derived SINR expression. Insights from the derived analytical results demonstrate that the ratio between the transmitter antenna number and the relay number is a dominate factor of the system performance. Afterward, the correctness of the derived expressions are verified by the Monte Carlo simulations with numerical results. Simulation results also illustrate that: 1) the transmitter antenna, averaged power value, and user number display the positive correlations on the capacity and sum rate performances, whereas the relay number displays a negative correlation on the performance and 2) the combined massive-MIMO-NOMA scheme is capable of achieving higher capacity performance compared with the conventional MIMO-NOMA, relay-assisted NOMA, and massive-MIMO orthogonal multiple access (OMA) scheme. [ABSTRACT FROM AUTHOR]

Small-cell networks and massive multiple-input multiple-output (MIMO) systems are regarded as important candidate techniques for 5G communication systems. This paper considers a heterogeneous network composed of a macrocell tier overlaid with an extremely dense tier of small-cells. In the network, the macrocell base station (BS), which applies massive MIMO, does not only serve macro user equipment units but also provides wireless backhaul for small-cell access points (APs). The wireless backhaul shares the same spectrum resource with radio access networks without creating extra spectrum resources. However, due to the densification of small-cells, the inter- and intra-tier interferences become severe. To mitigate the interferences, we use the regularized zero-forcing precoding combined with a projection technique is used at the BS in downlink (DL) to avoid interference to the APs in uplink (UL). Meanwhile, the joint linear minimum mean square error detection is applied in UL to mitigate the inter-tier interference. We derive deterministic expressions for ergodic UL and DL sum rates (SRs) by leveraging the large-dimensional random matrix theory. The expressions only depend on statistical channel information and can be used to optimize the bandwidth division between radio access links and wireless backhaul, as well as the time allocation between DL and UL operation intervals. Numerical results show that the deterministic SR equivalents are accurate and that the proposed resource allocation method can significantly improve system performance. [ABSTRACT FROM AUTHOR]

This paper considers the secrecy communication of a wirelessly powered network, where an energy-constrained legitimate transmitter (Alice) sends message to a legitimate receiver (Bob) with the energy harvested from a dedicated power beacon, while an eavesdropper (Eve) intends to intercept the information. A simple time-switching protocol with a time-switching ratio $\alpha $ is used to supply power for the energy-constrained legitimate transmitter. To improve the physical layer security, we first propose a protocol that combines maximum ratio transmission with zero-forcing (ZF) jamming for the case without Eve’s channel state information (CSI), i.e., Alice has access to Bob’s CSI only. Then, we propose a protocol that uses a ZF transmitting strategy to minimize the signal-to-noise ratio (SNR) at Eve for the case that Alice is capable of obtaining partial CSI related to Eve. Closed-form expressions and simple approximations of the connection outage probability and secrecy outage probability are derived for both protocols. Furthermore, the secrecy throughput as well as the diversity orders achieved by our proposed protocols are characterized, and the optimal time-switching ratio $\alpha $ and power allocation coefficient $\beta $ for secrecy throughput maximization are derived in the high SNR regime. Finally, numerical results validate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

Mutual coupling among receive antennas can profoundly reduce capacity in multiple-input, multiple-output (MIMO) systems. Prior work has shown that these losses can often be significantly reduced by using sophisticated antenna matching at the receiver. However, previous studies have focused exclusively on frequency non-selective matching, and rely on assumptions that are valid only for small bandwidths. In this paper, we consider the capacity of broadband MIMO-OFDM systems with coupled receive antennas. We present upper and lower bounds on the best capacity that can be achieved by physically realizable, frequency-selective antenna matching. The upper and lower bounds coincide for most antenna configurations considered in the examples, and thus determine the performance of capacity-optimal matching. These results suggest that frequency-selective matching can significantly increase capacity in the presence of strong coupling. Moreover, these gains can be achieved by a simple class of matching networks that are easily realized in hardware. [ABSTRACT FROM AUTHOR]

Massive multiuser (MU) multiple-input multiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang’s theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3–4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10−3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8 dB. [ABSTRACT FROM AUTHOR]

This paper addresses joint transceiver design for secure downlink communications over a multiple-input multiple-output relay system in the presence of multiple legitimate users and malicious eavesdroppers. Specifically, we jointly optimize the base station (BS) beamforming matrix, the relay station (RS) amplify-and-forward transformation matrix, and the covariance matrix of artificial noise, so as to maximize the system worst-case secrecy rate in the presence of the colluding eavesdroppers under power constraints at the BS and the RS, as well as quality of service constraints for the legitimate users. This problem is very challenging due to the highly coupled design variables in the objective function and constraints. By adopting a series of transformation, we first derive an equivalent problem that is more tractable than the original one. Then, we propose and fully develop a novel algorithm based on the penalty concave-convex procedure (penalty-CCCP) to solve the equivalent problem, where the difficult coupled constraint is penalized into the objective and the resulting nonconvex problem is solved at each iteration by resorting to the CCCP method. It is shown that the proposed joint transceiver design algorithm converges to a stationary solution of the original problem. Finally, our simulation results reveal that the proposed algorithm achieves better performance than other recently proposed transceiver designs. [ABSTRACT FROM AUTHOR]

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]

This paper proposes a synthetic statistical top-down MIMO power line communications channel model based on a pure phenomenological approach. The basic idea consists of directly synthesizing the experimental channel statistical properties to obtain an extremely compact model that requires a small set of parameters. The model is derived from the analysis of the in-home $2\times 3$ MIMO PLC channel data set obtained by the European Telecommunications Standards Institute specialist task force 410 measurement campaign in the band 1.8–100 MHz. The challenge of modeling the channel statistical correlation, exhibited among the frequencies and between the MIMO modes, in compact form is tackled and it is shown that a small set of parameters can be used to reconstruct such a correlation behavior. The model is validated and compared with the measured channels, showing a good agreement in terms of average channel gain, root-mean-square delay spread, coherence bandwidth, and channel capacity distribution. [ABSTRACT FROM PUBLISHER]

Magnetic induction (MI)-based communication systems have gained increased attention in recent years. Typical applications for these systems lie in the area of wireless power transfer, near-field communication (NFC), and wireless sensor networks in challenging environments. In this paper, a system for simultaneous wireless information and power transfer (SWIPT) using MI-based signal transmission is designed for supporting one data stream and multiple parallel power streams. One of the possible applications for this scheme is an NFC-based access point. The overall system is optimized to guarantee a certain quality-of-service for the data stream as well as a maximum sum receive power for all power receivers (max-sum problem) or a maximum receive power for the worst power receiver (max-min problem), respectively. Both optimization problems turn out to be non-convex, such that the optimum solution cannot be found with limited computational complexity. Hence, we provide efficient suboptimal solutions. In this context, a convex approximation of the transmit power constraint in MI-based multiple-input multiple-output systems turns out to be very useful. A very high achievable power efficiency renders the proposed MI-based SWIPT system very promising. [ABSTRACT FROM AUTHOR]

In this paper, we analytically study the performance of multiple-input multiple-output underwater wireless optical communication (UWOC) systems with ON–OFF keying modulation. To mitigate turbulence-induced fading, which is amongst the major degrading effects of underwater channels on the propagating optical signal, we use spatial diversity over UWOC links. Furthermore, the effects of absorption and scattering are considered in our analysis. We analytically obtain the exact and an upper bound bit error rate (BER) expressions for both optimal and equal gain combining. In order to more effectively calculate the system BER, we apply Gauss-Hermite quadrature formula as well as approximation to the sum of lognormal random variables. We also apply the photon-counting method to evaluate the system BER in the presence of shot noise. Our numerical results indicate an excellent match between the exact and upper bound BER curves. Also, a good match between the analytical results and numerical simulations confirms the accuracy of our derived expressions. Moreover, our results show that spatial diversity can considerably improve the system performance, especially for channels with higher turbulence, e.g., a $3\times 1$ multiple-input single-output transmission in a 25 m coastal water link with a log-amplitude variance of 0.16 can introduce 8 dB performance improvement at the BER of 10−9. [ABSTRACT FROM PUBLISHER]

This paper studies the recent novel multiple-input multiple-output transmission technique called quadrature spatial modulation (QSM), in underlay cognitive radio (CR) systems. In particular, a multi-antenna secondary transmitter (ST) communicates with a multi-antenna secondary receiver (SR) in the presence of a primary receiver (PR). Considering only the statistical knowledge of the ST-PR channel gain, the QSM-CR scheme is investigated using a mean value (MV)-based power allocation strategy referred to as MV-based scheme. Furthermore, assuming that the ST-PR channel gain is perfectly known, the QSM-CR scheme is investigated using a power allocation method based on instantaneous channel state information (CSI), referred to as CSI-based scheme. In each scheme, considering imperfect ST-SR channel estimation, we study the secondary system performance, where closed-form expressions for the average pairwise error probability ( \rm \overline PEP ) are derived over Rayleigh fading channels. A tight upper bounded average bit error rate is obtained using the derived \rm \overline PEP expression. Moreover, simple approximate expressions are obtained to get insights on the system diversity and channel estimation errors’ effects. Numerical results, which match with simulations, illustrate the robustness of QSM in enhancing the overall system performance in the presence of estimation errors. [ABSTRACT FROM PUBLISHER]

In this paper, we propose joint transceiver design algorithms for the full-duplex $K$ -pair multiple-input multiple-output interference channel with simultaneous wireless information and power transfer. To mitigate and exploit the complex interference, we consider two important utility optimization problems, i.e., the sum power minimization problem and the sum-rate maximization problem. In the first problem, our aim is to minimize the total transmission power under both transmission rate and energy harvesting (EH) constraints. An iterative algorithm based on alternating optimization (AO) and with guaranteed monotonic convergence is proposed to successively optimize the transceiver coefficients. The algorithm consists of three main steps, where the concave–convex procedure (CCCP), the minimum mean-square error (MMSE) criterion, and the semidefinite relaxation technique are, respectively, employed to compute the vectors of power splitting ratios, the receiving matrices, and the transmitting beamforming vectors. Two simplified algorithms based on fixed beamformers, namely, the maximum ratio transmission and the maximum signal-to-interference-leakage beamformers are also proposed. In the second problem, our aim is to maximize the sum-rate under additional power and EH constraints. Due to the highly non-convex nature of this problem, we first reformulate it into an equivalent-weighted MMSE problem by introducing suitable weight factors, such that the global optima of the two problems are identical. Then, by utilizing the concept of AO and CCCP, we show that the equivalent problem can be efficiently solved. Again, with the aid of the fixed beamformers, two simplified algorithms are provided to reduce the computational complexity. Simulation results are presented to validate the effectiveness of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a space time code construction with a symbol rate of two for free space optical multiple input multiple output (FSO-MIMO) communication systems. Unlike the radio-frequency space time coding design that deals with complex symbols holding phase and magnitude information, the phase detection in wireless optical communications remains very challenging. This restricts optical MIMO codes to carry positive magnitude information belonging to a finite range. To meet these requirements, we propose to design the FSO-MIMO codes considering first the whole real space \mathbb R , followed by a bipolar to unipolar conversion to fit in the intensity margin. We consider the MIMO configurations with two or four transmitters (lasers). We base our shape-preserving construction on quadratic extension fields that linearly combine the real symbols to form a full diversity space time code with a symbol rate equal to two. For each configuration, we show how to optimize the choice of the algebraic field numbers to jointly optimize the non-vanishing code determinant and the bipolar to unipolar attenuation factor. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of designing a linear precoder for multiple-input multiple-output (MIMO) systems in conjunction with quadrature amplitude modulation (QAM) is addressed. First, a novel and efficient methodology to evaluate the input-output mutual information for a general MIMO system as well as its corresponding gradients is presented, based on the Gauss-Hermite quadrature rule. Then, the method is exploited in a block coordinate gradient ascent optimization process to determine the globally optimal linear precoder with respect to the MIMO input-output mutual information for QAM systems with relatively moderate MIMO channel sizes. The proposed methodology is next applied in conjunction with the complexity-reducing per-group processing technique to both perfect channel state information (CSI) at the transmitter as well as statistical CSI (Statistical CSI) scenarios, with large transmitting and receiving antenna sizes, and for constellation size up to M = 64. We show by the numerical results that the precoders developed offer significantly better performance than the configuration with no precoder as well as the maximum diversity precoder for QAM with constellation sizes M = 16, 32, and 64 and for MIMO channel size up to 100 × 100. [ABSTRACT FROM PUBLISHER]

We consider the multiple-input multiple-output (MIMO) wiretap channel under a minimum receiver-side power constraint in addition to the usual maximum transmitter-side power constraint. This problem is motivated by energy harvesting communications with wireless energy transfer, where an added goal is to deliver a minimum amount of energy to a receiver in addition to delivering secure data to another receiver. In this paper, we characterize the exact secrecy capacity of the MIMO wiretap channel under transmitter and receiver-side power constraints. We first show that solving this problem is equivalent to solving the secrecy capacity of the wiretap channel under a double-sided correlation matrix constraint on the channel input. We show the converse by extending the channel enhancement technique to our case. We present two achievable schemes that achieve the secrecy capacity: the first achievable scheme uses a Gaussian codebook with a fixed mean, and the second achievable scheme uses artificial noise (or cooperative jamming) together with a Gaussian codebook. The role of the mean or the artificial noise is to enable energy transfer without sacrificing from the secure rate. This is the first instance of a channel model where either the use of a mean signal or the use of channel prefixing via artificial noise is strictly necessary for the MIMO wiretap channel. We then extend our work to consider a maximum receiver-side power constraint instead of a minimum receiver-side power constraint. This problem is motivated by cognitive radio applications, where an added goal is to decrease the received signal energy (interference temperature) at a receiver. We further extend our results to: requiring receiver-side power constraints at both receivers; considering secrecy constraints at both receivers to study broadcast channels with confidential messages; and removing the secrecy constraints to study the classical broadcast channel. [ABSTRACT FROM PUBLISHER]

In this paper, a low-complexity approach for the large-scale (underdetermined) multiple-input multiple-output (MIMO) detection is proposed using the Markov chain Monte Carlo (MCMC) algorithm in conjunction with blockwise sampling. Klein’s algorithm is employed in each sub-system to draw multidimensional samples for an MCMC detector in iterative detection and decoding (IDD). From analysis, we find that the lattice reduction (LR) technique cannot improve the performance of the proposed MCMC-based approach under low-correlated channel environment. In addition, due to blockwise sampling, the proposed method exhibits a faster convergence speed when running a Markov chain and provides a near-optimal performance for the detection of underdetermined MIMO systems. Complexity analysis and simulation results show that the proposed approach outperforms the conventional LR-based Klein randomized successive interference cancellation (SIC) detection with a relatively low complexity. [ABSTRACT FROM PUBLISHER]

Energy efficiency is a key enabler for the next generation of communication systems. Equally, resource allocation and cooperative communication are effective techniques for improving the communication system performance. In this paper, we propose an optimal energy-efficient joint resource allocation method for the multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) system. We define the joint source and multiple relays optimization problem and prove that its objective function, which is not generally quasiconvex, can be lower bounded by a convex function. Moreover, all the minima of this objective function are strict minima. Based on these two properties, we then simplify the original multivariate optimization problem into a single variable problem and design a novel approach for optimally solving it in both the unconstraint and power constraint cases. In addition, we provide a sub-optimal approach with reduced complexity; the latter reduces the computational complexity by a factor of up to 40 with a near-optimal performance. We finally utilize our novel approach for comparing the optimal energy-per-bit consumption of multi-hop MIMO-AF and MIMO systems; the results indicate that MIMO-AF can help to save energy when the direct link quality is poor. [ABSTRACT FROM PUBLISHER]

In this paper, a multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system, including one base station (BS) equipped with multiple antennas, one desired single-antenna information receiver (IR), and $N$ ( $N > 1$ ) single-antenna energy-harvesting receivers (ERs) is considered. Assuming that the information signal to the desired IR may be eavesdropped by ERs if ERs are malicious, we investigate the secrecy performance of the target MISO SWIPT system when imperfect channel state information (CSI) is available and adopted for transmit antenna selection at the BS. Considering that each eavesdropping link experiences independent but not necessarily identically distributed Rayleigh fading, the closed-form expressions for the exact and the asymptotic secrecy outage probability, and the average secrecy capacity are derived and verified by simulations. Furthermore, the optimal power splitting factor is derived for each ER to realize the tradeoff between the energy harvesting and the information eavesdropping. Our results reveal the impact of the imperfect CSI on the secrecy performance of MISO SWIPT systems in the presence of multiple wiretap channels. [ABSTRACT FROM PUBLISHER]

Although there has been a growing interest on the study of diversity-multiplexing tradeoff (DMT), the existing works are mostly restricted to the outcomes reported for Rayleigh, Rician, and Nakagami fading channels. In this paper, we investigate the optimal tradeoff in the presence of log-normal fading, which provides an accurate model for indoor wireless, optical wireless, and ultra-wideband channels. We consider a multiple-input multiple-output (MIMO) log-normal channel, derive the outage probability expression, and then present the asymptotical DMT expression. It is shown that the asymptotical maximum diversity gain tends to infinity with logarithm of signal-to-noise ratio (SNR). To have further insight, we normalize the DMT with that of single-input single-output case and express the relative asymptotical DMT of the MIMO log-normal channel as a function of the number of transmit and receive antennas. We further study DMT for finite SNRs and demonstrate convergence to the asymptotical case. Extensive numerical results are provided to corroborate the analytical derivation. [ABSTRACT FROM AUTHOR]

Recent advancements in self-interference (SI) cancellation capability of low-power wireless devices motivate in-band full-duplex (FD) wireless backhauling in small cell networks (SCNs). In-band FD wireless backhauling concurrently allows the use of the same frequency spectrum for the backhaul as well as access links of the small cells. In this paper, using tools from stochastic geometry, we develop a framework to model the downlink rate coverage probability of a user in a given SCN with massive multiple-input–multiple-output (MIMO)-enabled wireless backhauls. The considered SCN is composed of a mixture of small cells that are configured in either in-band or out-of-band backhaul modes with a certain probability. The performance of the user in the considered hierarchical network is limited by several sources of interference, such as the backhaul interference, small cell base station (SBS)-to-SBS interference, and the SI. Moreover, due to the channel hardening effect in massive MIMO, the backhaul links only experience long term channel effects, whereas the access links experience both the long term and the short term channel effects. Consequently, the developed framework is flexible to characterize different sources of interference while capturing the heterogeneity of the access and backhaul channels. In specific scenarios, the framework enables deriving closed-form coverage probability expressions. Under perfect backhaul coverage, the simplified expressions are utilized to optimize the proportion of in-band and out-of-band small cells in the SCN in the closed form. Finally, a few remedial solutions are proposed that can potentially mitigate the backhaul interference and in turn improve the performance of in-band FD wireless backhauling. Numerical results investigate the scenarios in which in-band wireless backhauling is useful and demonstrate that maintaining a correct proportion of in-band and out-of-band FD small cells is crucial in wireless backhauled SCNs. [ABSTRACT FROM AUTHOR]

Coarse quantization at the base station (BS) of a massive multi-user (MU) multiple-input multiple-output (MIMO) wireless system promises significant power and cost savings. Coarse quantization also enables significant reductions of the raw analog-to-digital converter data that must be transferred from a spatially separated antenna array to the baseband processing unit. The theoretical limits as well as practical transceiver algorithms for such quantized MU-MIMO systems operating over frequency-flat, narrowband channels have been studied extensively. However, the practically relevant scenario where such communication systems operate over frequency-selective, wideband channels is less well understood. This paper investigates the uplink performance of a quantized massive MU-MIMO system that deploys orthogonal frequency-division multiplexing (OFDM) for wideband communication. We propose new algorithms for quantized maximum a posteriori channel estimation and data detection, and we study the associated performance/quantization tradeoffs. Our results demonstrate that coarse quantization (e.g., four to six bits, depending on the ratio between the number of BS antennas and the number of users) in massive MU-MIMO-OFDM systems entails virtually no performance loss compared with the infinite-precision case at no additional cost in terms of baseband processing complexity. [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]

Optimal data detection of data transmitted over a linear channel can always be implemented through the Viterbi algorithm (VA). However, in many cases of interest the memory of the channel prohibits direct application of the VA. A popular and conceptually simple method in this case, studied since the early 1970s, is to first filter the received signal in order to shorten the memory of the channel, and then to apply a VA that operates with the shorter memory. We shall refer to this general concept as a channel shortening (CS) receiver. Although studied for almost four decades, an information theoretic understanding of what such a simple receiver solution is actually doing is not available. In this paper, we show that an optimized CS receiver has a direct correspondance to the chain rule of mutual information. Furthermore, we show that the tools for analyzing the ensuing achievable rates from an optimized CS receiver are precisely the same as those used for analyzing the achievable rates of a minimum mean-square-error (MMSE) receiver. [ABSTRACT FROM AUTHOR]

This paper studies two-user cognitive multiple-input multiple-output (MIMO) interference channel with delayed channel state information at transmitter (CSIT), where a transmitter possesses noncasual knowledge of data originating at the other user. We first derive an upper bound of degrees-of-freedom (DoF) region and then propose DoF bound achieving schemes for various antenna configurations. Since interference condition and interference suppression capability vary with antenna configurations, the proposed DoF optimal schemes differently utilize cognitive transmission based on delayed CSIT to suppress interference and thus differ in the required numbers of time slots and transmit symbols, although the key idea of swapping interfering signals between users is common. Comparing with the DoF regions of relevant channels, we identify and analyze the contributions of cognitive transmission and delay CSIT toward enlarging the DoF region. Our analysis specifies antenna configurations where delayed CSIT and cognitive transmission are useful, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a new compressive sensing-based downlink channel state information (CSI) estimation scheme for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. The proposed scheme, which involves two-stage weighted block \ell _1-minimization, exploits the block sparse nature of the angular domain representation of the MIMO channel matrices and the existence of common scattering paths in the realistic propagation environment. In the first stage of the implemented scheme, a conventional block \ell _1-minimization program is solved to extract the information about the common/individual supports of the multiuser channel matrices. In the second stage, a weighted block \ell _1-minimization algorithm, the weighting coefficients of which are suitably chosen to exploit the acquired support information, is used to estimate the channel matrices. The analytic performance guarantees of the proposed scheme are specified based on the block restricted isometry property of the sensing matrix. Specifically, the upper bounds of the \ell _2-norm reconstruction error are derived using various assumptions regarding the weighting. The obtained analytical results enable a discussion of the selection of weighting coefficients to enhance the CSI estimation performance, and the determination of a sufficient condition under which the proposed scheme outperforms the unweighted naive solution. Computer simulations show that the proposed method achieves higher estimation accuracy as compared to an existing greedy-based algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a codeword refinement technique called double codeword coding in the context of MIMO feedback. In the proposed method, the second codeword is fed back in addition to the best codeword as their interpolation at the transmitter improves the channel knowledge. The derivation of the optimal interpolation parameter is presented together with the derivation of an upper-bound to the interpolation parameter based on channel quality feedback available at the transmitter. We show that double codeword feedback refinement has slightly lower complexity than alternative techniques and still achieves similar performance. Furthermore, double codeword coding can be generalized to higher transmission ranks. Using extended multiuser MIMO link simulations, we verify that the double codeword feedback is able to provide significant gains in 3GPP LTE context. [ABSTRACT FROM AUTHOR]

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]

Massive multiple-input multiple-output (MIMO) communication is an emerging technology that uses an excess of transmit antennas to realize high spectral efficiency. Achieving potential gains with large-scale antenna arrays hinges on sufficient channel estimation accuracy. Much prior work focuses on time-division duplex (TDD)-based networks, relying on reciprocity between the uplink and downlink channels. However, most currently deployed commercial wireless systems are frequency-division duplex (FDD)-based, making it difficult to exploit channel reciprocity. In massive MIMO FDD systems, the problem of channel estimation becomes even more challenging due to the substantial training resources and feedback requirements which scale with the number of antennas. In this paper, we consider the problem of training sequence design and the mapping of training signals to training periods. We focus on reduced-dimension training sequence designs, along with transmit precoder designs, aimed at reducing both hardware complexity and power consumption. The resulting designs are extended to hybrid analog-digital beamforming systems, which employ a limited number of active RF chains for transmit precoding, by applying the Toeplitz distribution theorem to large-scale linear antenna systems. A practical guideline for training sequence parameter selection is presented along with performance analysis. [ABSTRACT FROM AUTHOR]

Common signals in public channels of cellular systems should be transmitted omnidirectionally from the base station (BS) to ensure cell-wide coverage. In this paper, we propose an omnidirectional precoding (OP) based transmission for public channels in massive MIMO systems, which leads to a significant reduction in the downlink pilot overhead while providing omnidirectional signaling. For this OP based transmission, we present three necessary conditions that the OP matrix should satisfy, to meet the requirements for omnidirectional transmission for reliable cell-wide coverage, equal average power on each antenna to sufficiently utilize all the available power amplifier capacities of BS antennas, and achievable ergodic rate maximization for the i.i.d. channel, respectively. Then, several examples of the OP matrix satisfying the three necessary conditions simultaneously are designed by utilizing the Zadoff-Chu sequence and its properties. We also analyze the system performance in terms of achievable ergodic rate, outage probability, and peak-to-average power ratio (PAPR) for these designs. It is shown that a dedicated design of the OP matrix has the following advantages: 1) it asymptotically maximizes the achievable ergodic rate, maximizes the achievable diversity order, and minimizes the outage probability in the large-scale array regime, not only for the i.i.d. channel, but also for spatially correlated channels; 2) it preserves the PAPR of the transmitted signal after precoding. [ABSTRACT FROM AUTHOR]