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The paper studies a reconfigurable intelligent surface (RIS)-assisted multi-user uplink massive multiple-input multiple-output (MIMO) system with imperfect hardware. At the RIS, the paper considers phase noise, while at the base station, the paper takes into consideration the radio frequency impairments and low-resolution analog-to-digital converters. The paper derives approximate expressions for the ergodic achievable rate in closed forms under Rician fading channels. For the cases of infinite numbers of antennas and infinite numbers of reflecting elements, asymptotic data rates are derived to provide new design insights. The derived power scaling laws indicate that while guaranteeing a required system performance, the transmit power of the users can be scaled down at most by the factor $\frac{1}{M}$ when $M$ goes infinite, or by the factor $\frac{1}{MN}$ when $M$ and $N$ go infinite, where $M$ is the number of antennas and $N$ is the number of the reflecting units. Furthermore, an optimization algorithm is proposed based on the genetic algorithm to solve the phase shift optimization problem with the aim of maximizing the sum rate of the system. Additionally, the optimization problem with discrete phase shifts is considered. Finally, numerical results are provided to validate the correctness of the analytical results. [ABSTRACT FROM AUTHOR]

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

This paper investigates a point-to-point millimeter-wave (mmWave) massive MIMO system in which the transmitter and receiver consist of $K_t$ and $K_r$ distributed antenna subarrays, respectively. All the subchannel matrices between each pair of subarrays at the transmitter and the receiver are assumed to be mutually independent and known at the transmitter and the receiver. To quantify the potential of spatial multiplexing in such a system, the multiplexing gain is defined and analyzed when the numbers of antennas at subarrays go to infinity while the transmit power is held fixed. In particular, assuming that all subchannels have the same average number of propagation paths $\bar{L}$ , the paper shows that an average maximum multiplexing gain of $K_rK_t\bar{L}$ can be achieved. This result means that the multiplexing gain under a distributed array architecture can statistically increase in proportion with $K_rK_t$. The multiplexing gain analysis is also extended to the multiuser scenario. Simulation results obtained with the hybrid analog/digital processing finally corroborate the analytical results. [ABSTRACT FROM AUTHOR]

This paper addresses the channel estimation issue for millimeter wave (mmWave) massive MIMO systems with lens antenna array. Firstly, we formulate the channel estimation problem into the framework of sparse signal recovery. The formulation takes into account of the energy focusing property of the lens antenna array as well as the mutipath sparsity in mmWave MIMO channels. Then we develop an expectation maximization (EM) based algorithm to learn the parameters in the formulation, thereby fulfilling the channel estimation. Finally, we conduct simulations to verify the advantages of the proposed scheme over the state-of-the-art counterparts. [ABSTRACT FROM AUTHOR]

Multiple signal classification (MUSIC) has been widely applied in multiple-input multiple-output (MIMO) receivers for direction-of-arrival (DOA) estimation. To reduce the cost of radio frequency (RF) chains at millimeter-wave bands, hybrid analog-digital structure has been adopted in massive MIMO transceivers. In this situation, received signals at the antennas are unavailable to the digital receiver, and as a consequence, the spatial covariance matrix (SCM), which is essential in MUSIC algorithm, cannot be obtained using traditional sample average approach. Based on our previous work, we propose a novel algorithm for SCM reconstruction in hybrid massive MIMO systems with multiple RF chains in this paper. By switching the analog beamformers to a group of predetermined DOAs, SCM can be reconstructed through the solutions of a set of linear equations. Furthermore, a low-complexity algorithm, as well as a careful selection of the predetermined DOAs, will be also presented in this paper. Simulation results show that the proposed algorithms can reconstruct the SCM accurately so that MUSIC algorithm can be well used in hybrid massive MIMO systems with multiple RF chains. [ABSTRACT FROM AUTHOR]

Even if massive multiple-input multiple-output (MIMO) can theoretically bring huge benefits, it incurs substantial hardware complexity and expensive hardware costs. To address these issues while maintaining the system performance simultaneously, we develop an asymmetrical transceiver architecture for massive MIMO systems in this paper by releasing the shackles on radio frequency (RF) chains. Specifically, we first develop the architecture for the asymmetrical transceiver where the number of receive RF chains is different from that of the transmit RF chains. Due to this unequal number of RF chains, channel inconsistency appears. To overcome the channel inconsistency and thus fully harness the system's downlink data transmission capability, we propose two uplink-to-downlink channel transfer algorithms. The cost and power consumption models for the asymmetrical transceiver are also developed and the uplink signal-to-noise loss due to the channel inconsistency is investigated. Through analyzing system spectral, cost, and energy efficiency, we demonstrate that the proposed asymmetrical transceiver-based massive MIMO system can achieve excellent downlink spectral efficiency while maintaining a reasonable energy efficiency. [ABSTRACT FROM AUTHOR]

As one of the three main application scenarios of 5 G cellular system, massive Machine-Type Communications (mMTC) has been regarded as the key solution to facilitate the IoT paradigm. One major bottleneck for accommodating mMTC is the severe congestion at the cellular random access channel when plenty of Machine-Type Devices (MTDs) send access requests concurrently while the preamble resources are limited. To remedy this issue, limiting the number of retransmissions and dropping access requests after the limit is reached can be an effective approach. Yet, the effect of the preamble retransmission limit $K$ on the optimal access performance of mMTC in cellular networks remains largely unexploited, which motivates the study in this paper. Specifically, in this paper, we start by characterizing the network steady-state points based on the limiting probability of successful transmission of access requests. We then obtain explicit expressions of the access throughput and the mean access delay of successfully-transmitted access requests as functions of $K$ and the number of preambles $M$. The maximum access throughput and the corresponding optimal backoff window size are further derived. It is shown that the maximum access throughput is independent of $K$ , while the mean access delay can be significantly reduced with a small $K$ , yet, at the expense of increased request dropping ratio. In addition, to improve both the throughput and delay performance, the analysis shows that more preambles should be allocated but the performance gain becomes marginal when $M$ is large. Therewith, an algorithm is proposed for determining the least number of preambles $M^\ast$ that maximizes the access throughput and the preamble resource utilization ratio. Numerical results show that a smaller preamble retransmission limit $K$ can further reduce $M^\ast$. [ABSTRACT FROM AUTHOR]

In this paper, for an overlay cognitive radio system in which the primary users’ information exchange is assisted by a secondary multiple-input multiple-output two-way relay network, we propose two spectrum sharing schemes that achieve the full diversity gain in both the primary and secondary networks. In the spectrum sharing problem that we formulate, there are two degrees of freedom to be optimized: relay selection and spectrum allocation. We jointly optimize these two degrees of freedom such that the achievable rate in the secondary network is maximized under the constraint that a minimum quality of service requirement in terms of the achievable rate is satisfied for the primary network. We analyze the performance of the proposed schemes in terms of the outage probability (that reflects the rate of unsuccessful spectrum sharing), the asymptotic behavior and the diversity order over Rayleigh fading channel. The analysis of the paper shows that in both of the proposed schemes, the full diversity of order $N M^2$ is achieved by the primary users, where $N$ is the number of the secondary users and $M$ is the number of antennas per terminal. Moreover, in both of the schemes, the full selection diversity of order $N M^2$ is guaranteed for the secondary network. We also provide extensive simulation results to confirm the theoretical analysis of this paper. [ABSTRACT FROM AUTHOR]

This correspondence paper studies the impact of nonidentically distributed channel estimation error on performance of a scheduled space-time block coding with mean-value power allocation in cognitive-radio multiple-input multiple-output system. Using the derived probability density function, the exact closed-form expressions of the proposed system for outage probability, ergodic capacity, and symbol-error rate (SER) with both $\rm M$ -ary quadrature amplitude modulation and phase shift keying modulation are derived. Using asymptotic analysis, this paper quantifies the diversity order for both outage probability and SER in the presence of nonidentically distributed error. From the analysis results, this paper shows that the diversity order is enhanced by the multiuser diversity as the number of user terminals increases regardless of outage probability and SER, while the spatial diversity is eliminated. [ABSTRACT FROM AUTHOR]

This paper investigates the performance analysis of dual selection (i.e., combining user selection and transmit antenna selection) with maximal ratio combining (MRC) over nonidentical imperfect channel estimation in a multiple-input multiple-output system. This paper derives the exact and approximate cumulative density function and probability density function (PDF) for the dual selection with MRC over nonidentical imperfect channel estimation. Using the distribution, the exact and approximate closed-form expressions of the outage probability are derived with quantification of diversity order. Further, this paper derived the exact ergodic capacity and approximate outage capacity of the the dual selection via Gaussian and Gamma approximations. The numerical results show that the capacity of the dual selection with MRC is enhanced by the number of receive antennas as well as the number of user terminals and sum of channel correlation coefficients, while the order of the receive spatial diversity for outage probability is eliminated by the nonidentical channel estimation error. [ABSTRACT FROM AUTHOR]

Millimeter-wave vehicle-to-vehicle communication systems with multiple-input multiple-output antenna array have drawn significant attention because it is expected to satisfy the growing bandwidth requirements for the cooperative intelligent transportation systems. However, maintaining high-quality communication links between communicating vehicles without high overhead is a challenging problem due to the high mobility of vehicles. In this paper, we propose a beam management algorithm with spatially distributed antenna subarrays instead of a single co-located antenna array. Unlike existing methods, we use distributed antenna subarrays to exploit the geometric relationship of the beam directions and the relative distance between communicating vehicles. We reduce the beam alignment errors by minimizing the sum of squared errors between the estimated beam direction after the beam training process and the refined beam direction derived from the measured position and velocity data. Additionally, a position data request protocol is devised to reduce the beam refining errors. Numerical results demonstrate that the proposed beam management algorithm successfully reduces the beam alignment errors and it is robust to position and velocity measurement errors. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) frequency spectrum offers orders of magnitude greater spectrum to mitigate the severe spectrum shortage in conventional cellular bands. To overcome the high propagation loss in the mmWave band, massive multiple-input and multiple-output (MIMO) can be adopted at both transmitter and receiver to provide large beamforming gains. At the same time, hybrid architecture is applied to reduce the huge power consumption caused by devices operating at radio frequency (RF). However, because of the hybrid architecture and large number of antennas, it is hard to obtain the channel state information (CSI) which is crucial for obtaining desirable beamforming gains. Off-grid error and sparsity pattern (SP) estimation error are two main limiting factors of the performance of most existing compressive sensing (CS) based channel estimation (CE) algorithms. Off-grid error presents when the true angle does not lie on the discretized angle grid of mmWave channel in the spatial domain. In this paper, we first propose a fast Bayesian matching pursuit method with ‘virtual sparsity’ to improve the accuracy of SP estimation and name it as the improved Bayesian matching pursuit (IBMP). Then an enhanced algorithm, named off-grid IBMP (OG-IBMP), is developed to mitigate the off-grid problem, followed by a theoretical analysis of OG-IBMP. This method iteratively updates the selected grid points and updates the corresponding parameters based on the maximum a posteriori (MAP) criterion. Numerical simulations are performed to validate our theoretical analysis and evaluate the performance of the proposed method. Compared to other existing methods, the results show that our proposed OG-IBMP algorithm greatly reduces the off-grid error and significantly enhances the accuracy of the SP estimation with low computational complexity. [ABSTRACT FROM AUTHOR]

This paper examines the multiple-input multiple-output (MIMO) characteristics of the vehicular MIMO channel at 5.9 GHz by analyzing the correlation of multipath components (MPCs) in the case of high antenna separation and the angular characteristics of the same scenario. The scenario is selected as crossing traffic on urban intersections. The 2 $\times$ 2 channel measurements with a wideband channel sounder are employed for the correlation analysis, and in parallel, the same scenario is simulated with a ray-tracing tool for the analysis of the angular domain. We introduce measures and tools to describe the relevant characteristics and the performance; the limitations of the ray-tracing simulation are also subdued to critical evaluation. The focus of this paper is set on the evaluation of the presented method on one selected experiment (combination of measurement and ray-tracing simulation) rather than on an exhaustive statistical analysis of many scenarios. The combination lies in the higher level of analyzing the MIMO characteristics of the channel using two different methods. The results provide that the MIMO channels show a similar power level in terms of mean MPC power, but the linear correlation stays relatively low. Specifically, discrete MPCs tend to be more highly correlated than diffuse MPCs. Furthermore, the angular spread is highly dynamic but small and substantially increases when both vehicles are near the center of the intersection. Significant power contributions caused by buildings along the roadside are identified. [ABSTRACT FROM AUTHOR]

Previous correlation-based wideband multiple-input–multiple-output (MIMO) channel models have been limited to non-line-of-sight (NLoS) scenarios where simple antenna correlation measurements are sufficient to describe the correlated Gaussian process representing the fading statistics. However, in the presence of line-of-sight (LoS) or specular reflections, simple antenna correlation measurements unfortunately do not lead to accurate fading characterizations. In this paper, we propose a trend-stationary correlation-based analytical model for wideband LoS and NLoS MIMO channels and design and validate a wideband multitone MIMO channel sounder and estimator to, respectively, measure channel impulse responses (CIRs) and estimate channel parameters for this model. Joint maximum-likelihood (ML) estimation of the LoS component and the NLoS complex correlation matrix is presented. In addition to enabling the estimation of the path correlation matrix of a wireless channel in the presence of LoS components, the modeling approach also provides tools to evaluate the validity of the assumption of uncorrelated scattering (US), even in LoS environments, which is commonly used in channel modeling. A more general model that does not assume US is also presented, which can likewise be estimated using the proposed estimator. To validate the channel sounding/model estimator techniques, we employ channel sounding waveforms and collect snapshots from the outputs of a state-of-the-art hardware MIMO channel emulator capable of emulating multipath channels under the US assumption. Receiver signal processing and channel parameter estimation are performed on the collected data, and the results are compared with the emulated channel parameters. The work is unique in that it provides a correlation-based multipath MIMO channel modeling approach that addresses LoS environments, it describes corresponding estimation techniques to extract the full complex correlation matrix, and the model estimators are backed using channel sounding with emulation-based validation. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate a two-hop simultaneous wireless information and power transfer (SWIPT) amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay communication system with an energy-limited relay node. The relay node harvests energy based on the radio-frequency (RF) signal transmitted from the source node through the time-switching (TS) protocol and fully uses the harvested energy to precode and forward the information to the destination node. The non-linear energy harvesting models are considered at the relay node. With the consideration of the channel estimation error, the joint optimization of the TS factor, source and relay precoding matrices is proposed with robustness against the channel state information (CSI) mismatch to maximize the mutual information (MI) between the source and destination nodes. The optimal structure for the source and relay precoding matrices is derived to simplify the transceiver optimization problem. Numerical simulations show that the system performance provided by the proposed algorithms with robustness is better than the non-robust algorithm. [ABSTRACT FROM AUTHOR]

As the number of antennas increases, the massive multiple-input multiple-output (MIMO) system can precisely point to user equipments (UEs) with narrow beams. Accurate and timely channel state information (CSI) feedback is crucial to keep UEs in service. Mobile UEs, however, may suffer from the narrow beam nature of the massive MIMO system since UEs can move out of the beam coverage. When intelligent reflecting surface (IRS) is applied to the massive MIMO system, the adjustment of the IRS cannot be frequent as the IRS is controlled remotely by the base station (BS). Limiting the number of CSI feedback and the number of both BS and IRS adjustments significantly reduces the overhead of transmission and computation to the system. In this paper, we consider the UEs’ mobility adaptation problem in an IRS assisted multiuser massive MIMO downlink system with infrequent CSI feedback. We propose a beam control method that adapts to UEs’ mobility. The problem is constructed as a sum rate problem where both the BS and IRS are taken into account to jointly optimize the beamforming matrices. Simulation results show that our proposed algorithm can converge quickly and provide satisfactory performance for mobile UEs. At the same time, our proposed algorithm reduces the frequency of updating the beamforming matrices effectively both at the BS and at the IRS. [ABSTRACT FROM AUTHOR]

In multi-user multiple-input multiple-output (MIMO) systems, a base station requires downlink channel state information for each user to suppress interferences. In time-varying environments, however, channels at the actual transmission time differ from the estimated ones because we have delay. This causes interference and deteriorates the packet error rate performance. To overcome this problem, we previously proposed a channel prediction method based on direction of arrival (DOA) estimation of multipath components obtained with a compressed sensing technique. This method can predict channels with high accuracy when we can assume that user equipment alone moves and the surrounding scatterers are stationary. In real environments, however, this assumption does not hold, and this method cannot be applied. In this paper, we propose a prediction method using two-step compressed sensing without the above assumption. In the first step, we estimate the DOAs of multipath signals. In the second step, we estimate the Doppler frequencies and their complex amplitudes using the estimated DOA information. From these values, we predict the MIMO channels at the actual transmission time. We discuss the performance of this method in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes a framework to construct 3-D complementary codes (3DCCs), which enable chip-level space–time coding to integrate multiantenna and multiple-access techniques in a unified platform. The 3DCCs are generated based on an extension method with the help of traditional complementary codes and well-designed matrices. The relationship between the correlation properties and flock size of the constructed 3DCCs is analyzed, and the proposed framework provides a generic way to construct different families of 3DCCs with a controllable tradeoff between their correlation properties and flock sizes. As examples, three families of 3DCCs with different characteristic features are constructed using the framework, and their correlation properties are simulated to validate their properties. The general architecture of the 3DCC-based multiple-input multiple-output (MIMO) system is also proposed in this paper. The simulated bit-error-rate (BER) performance of the corresponding system over both flat and multipath fading channels show that the constructed 3DCCs can eliminate both multiuser and multipath interferences in multiuser MIMO communications. The property to provide both transmit diversity and multiplexing with its uniquely flexible tradeoff between the two also makes it particularly well suited for futuristic wireless communications to fit to varying channel conditions and application requirements. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate antenna selection (AS) methods for bidirectional (BD) full-duplex multiple-input–multiple-output (MIMO) systems in which antennas at each node can be selected to either transmit or receive. In this configuration, we first analyze the average sum rate of the optimal AS scheme that finds the best antenna set solution by examining all the possible candidates. The result provides insight into which transmit and receive antenna configuration improves the average sum-rate performance of the AS scheme. Then, we present a new AS algorithm that achieves near-optimal sum-rate performance with much reduced complexity compared with the optimal AS scheme. From simulation results, we verify that our sum-rate analysis for the optimal AS scheme matches the numerical results and confirm that, by employing the proposed AS algorithm, a performance gain of 15% is achieved. [ABSTRACT FROM PUBLISHER]

This paper studies the electronically steerable parasitic array radiator (ESPAR) antenna as a solution for beam pattern switching to implement blind interference alignment (BIA). The ESPAR antenna uses a single radio-frequency (RF) chain, and its beamforming is achieved by simply tuning the reactance loads of parasitic elements. Furthermore, ESPAR's beam pattern can be designed to enhance the received signal-to-noise ratio (SNR), thereby improving the performance of BIA. The focus of this work is the design of the ESPAR beam pattern to realize and improve BIA. In the first approach, each receiver ESPAR antenna dynamically selects the proper beam patterns from among the sector beam patterns, which are pre-designed to access different angular sectors with constant optimal antenna efficiency. We also propose a singular value decomposition (SVD) beamforming method, by means of the available channel state information at the receiver and a dynamic matching network for a high antenna efficiency. The simulation results illustrate the improvement of BIA with proposed methods, especially in the low and moderate SNR region, due to ESPAR's beamforming capability. [ABSTRACT FROM PUBLISHER]

This paper analyzes the ratio of transmit antennas to receive antennas at the base station (BS) in full-duplex multiuser multiple-input–multiple-output (MU-MIMO) systems with large-array BS and half-duplex multiantenna users. We consider a full-duplex BS with a block diagonalization (BD) precoder for downlink transmission and a BD receive filter for uplink reception. We derive the approximated downlink sum-rate considering the inter-user interference, and the uplink sum-rate considering the self-interference (SI), for large numbers of BS antennas. Based on the analysis, we formulate an optimization problem in terms of the ratio of transmit antennas to receive antennas to maximize the sum-rate. The analysis shows that the antenna ratio for maximizing the sum rate converges to the ratio of downlink streams to uplink streams as the number of total BS antennas goes to infinity. Simulation results confirm the analysis and show that the BS using the derived antenna ratio in the full-duplex MU-MIMO system can achieve about a 10∼20 b/s/Hz performance gain compared with the BS using an equal number of transmit and receive antennas. [ABSTRACT FROM PUBLISHER]

Wireless systems employing frequency-division duplexing (FDD) must use duplexing filters to isolate the sensitive receiver from its own strong transmission. The number of filters in the duplexer is equal to the total number of aggregated transmit and receive bands. These filters are nontunable; therefore, a separate duplexer is required for each combination of operating bands. This paper presents an adaptive duplexer architecture capable of handling more than one receiver channel and tunable over a wide frequency range. The structure uses a combination of a low-isolation device with multiple analog canceling loops controlled by a normalized least mean squares (N-LMS) algorithm to track changes in signal leakage. The control is a multiple-input–multiple-output (MIMO) problem. This paper shows that modeling the inverse plant can orthogonalize the problem and dramatically improve convergence times with reduced complexity over previous search algorithms. Low-power pseudonoise (PN) pilot signals are proposed to detect and cancel the transmitter noise. Simulations show that 50 dB of isolation is possible with 20-MHz Long-Term Evolution (LTE)-like channels. Convergence takes 80 iterations (10 ms) from cold or 15 iterations (1.5 ms) for changes in carrier frequency or antenna loading. [ABSTRACT FROM PUBLISHER]

A zero forcing (ZF) assisted single layer beamforming is developed for spatial modulation (SM) and space shift keying (SSK) modulation multiple input multiple output (MIMO) systems, termed as SZF-SM/SZF-SSK, to achieve both transmit beamforming and receive diversity gain in this paper. Specifically, the proposed SZF-SM/SZF-SSK maps part of the bits to spatial domain, simultaneously forming a ZF precoding assisted single layer data both in multiple input single output (MISO) and MIMO systems, that differs greatly from conventional ZF beamforming assisted MIMO systems. With MISO configuration, the ZF precoder of SZF-SM/SZF-SSK converges to the maximum ratio transmission (MRT), achieving only the transmit beamforming gain. With MIMO configuration, SZF-SM/SZF-SSK tranceiver could be further modified along with the MIMO channel to achieve single layer transmission and joint detection, attaining both the transmit beamforming and receive diversity gain in SM-MIMO system. The theoretical analysis and the simulation results of the proposed SZF-SM/SZF-SSK with MISO and MIMO configurations are presented in this paper respectively, which show an attractive performance gain over the conventional SM/SSK. Compared with the conventional ZF beamforming assisted MIMO systems and some other CSI assisted SM-MIMO schemes, the proposed scheme exhibits better performance, especially under highly correlated MIMO channels, rendering a new and practical way to achieve low rank MIMO transmission with good performance and high data rate. [ABSTRACT FROM AUTHOR]

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

This paper presents multi-user (MU) linear precoding methods for massively distributed antenna system (DAS) with polarized antennas, where mobile stations (MSs) are spatially grouped and the distributed antenna (DA) ports with a polarized-antenna are connected to a central base station (BS). While the (slowly-changing) long-term channel state information (CSI) (i.e., large scale fading and polarization) can be accurately estimated at the transmit-side, the short-term CSI (instantaneous channel response) is available at the transmit-side with quantization errors due to the limited feedback. Accordingly, the utilization of a large number of DA ports is not always beneficial due to the imperfect short-term CSI at the transmitter (CSIT). In this paper, we first derive the asymptotic achievable rate and signal-to-leakage-and-noise ratio (SLNR) for the MU linear precoding in the massive DAS, which depends on the long-term CSIT and the number of feedback bits, and propose a transmit DA port selection based on the asymptotic SLNR performance. Here, the number of selected DA ports can be also optimized according to the long-term CSIT and the number of feedback bits. Furthermore, we also propose a polarization selection strategy at each DA port (equipped with multi-polarized antennas) so as to exploit the polarization diversity. Through the simulation, we confirm that the proposed MU precoding with the DA port selection outperforms the conventional precoding schemes for the DAS and, furthermore, the proposed polarization selection strategy achieves a rate performance comparable to the DAS with a (single polarized antenna) node density twice as large. [ABSTRACT FROM AUTHOR]

In a time-division duplex (TDD) massive multiple-input multiple-output (MIMO) system, the number of available orthogonal pilot sequences in each cell is limited. In this paper, we consider a massive MIMO system where the number of available orthogonal pilot sequences is less than the number of users. In order to optimize the long-term performance in estimating the uplink (UL) channels, the base station (BS) needs to judiciously decide the allocation of the available pilot sequences to different users in each training phase. In this paper, the pilot allocation problem is modeled as a partially observable Markov decision process with an exploitation-exploration tradeoff under the Gauss-Markov fading channels. We then investigate this problem within the restless multi-armed bandit (RMAB) framework and put forward a low-complexity method to derive the Whittle's index approximately. A simple index policy is then proposed to allocate the orthogonal pilots in a massive MIMO system. Numerical results demonstrate the superiority of the proposed index policy. [ABSTRACT FROM AUTHOR]

In this paper, we consider a single-relay-based decode-and-forward (DF) cooperative multiple-input multiple-output (MIMO) system in which the source, the relay, and the destination are equipped with Ns, Nr, and Nd antennas, respectively. We propose a joint antenna and path selection scheme, which jointly selects the single-transmit and single-receive antenna pairs, along with the selection of either a direct path that consists of source–destination channels or a cooperative path that consists of source–relay and relay–destination channels. The proposed selection scheme is based on the maximization of minimum of maximums (max-min-max) criterion of instantaneous signal-to-noise ratio (SNR). The analysis in this paper is based on the assumptions that all the channels follow independent Rayleigh fading. A closed-form expression of the symbol error rate (SER) for the proposed scheme in a cooperative MIMO system with M-ary phase-shift keying is derived. We extract the analytical diversity order from the derived SER and show that the proposed selection scheme achieves the diversity order of N_{s}N_{d}+N_{r}\mathrm{min}(N_{s},N_{d}) in the considered cooperative MIMO system. Closed-form expressions of bandwidth efficiency (BE) and ergodic capacity (C_{t})$ are derived for the proposed scheme. An optimized selection parameter from the specific set of values is numerically evaluated by maximizing a heuristic utility function (C_{t}\times \mbox{BE}/\mbox{SER}). By using the already-gathered information about the maximum instantaneous SNR of every hop, a power adaptation scheme that maximizes the instantaneous SNR in the cooperative path is proposed and analyzed. The proposed power adaptation scheme, which is applied only in the event of selection of a cooperative path, outperforms the uniform-power-distribution-based DF cooperative MIMO system. [ABSTRACT FROM AUTHOR]

This paper concerns the uplink of multicell multiuser multiple-input multiple-output (MIMO) systems. To tackle the effect of pilot contamination that is generally viewed as a bottleneck in previous work, this paper presents a superimposed pilot (SP)-aided uplink channel estimation scheme and mathematically characterizes the impact that an SP has on the performance of such a very large MIMO system. It is shown that there are two types of interference components that do not vanish, even when the number of antennas $M$ grows to infinity. The first type, which is referred to as cross-contamination, is due to the correlation between the SP and data among different cells. The second type, which is referred to as self-contamination, is due to the dependence between channel estimation and estimation error. Cross-contamination is, in principle, similar to pilot contamination in a conventional pilot-based multicell MIMO system, whereas self-contamination is unique for the SP-aided scheme. Both theoretical and simulation results demonstrate that the SP-aided scheme can effectively reduce the estimation contamination by increasing the data frame size and, in turn, achieve a significant improvement over the spectral efficiency, in comparison with conventional pilot-based methods. [ABSTRACT FROM AUTHOR]

This paper proposes a method of implementing analog eigenmode transmission for a short-range multiple-input–multiple-output (SR-MIMO) system that uses only 180° hybrid couplers. If the short-range MIMO system places transmitting and receiving arrays in line-of-sight (LOS) and symmetrically with respect to specific reference planes, the channel matrix in the system also becomes symmetrical. This allows the channel matrix to be diagonalized by connecting 180° hybrid couplers to both ports at the transmitter and receiver sides, i.e., eigenmode transmission can be realized. In this paper, first, the theory of the proposed technique is explained by taking a 2 $\times$ 2 MIMO as an example, based on the characteristics of 180° hybrid coupler and the theory of the cascade-connected network. Moreover, an extension to the method that offers 4 $\times$ 4 MIMO is also proposed. This paper clarifies that this proposed technique can diagonalize the channel matrix, regardless of array configuration, such as type of antennas and antenna spacing, as long as the symmetry of the system configuration is assured. Furthermore, numerical results verify that the distance between the transmitter and the receiver has no effect on channel orthogonality. As a result, this technique partially avoids the performance degradation caused by array displacement, which is a major disadvantage of the conventional analog-beamforming-based decoding technique for short-range MIMO systems. Thus, the superiority of the proposed technique is clear. [ABSTRACT FROM PUBLISHER]

Precoding-aided spatial modulation (PSM) is a multi-antenna communication scheme, which jointly modulates information bits into both the spatial index and the signaling constellation. Specifically, the spatial bits are conveyed by the index of a receive antenna, which is steered at by precoding at the transmitter. In this paper, the indices of the receive antennas are called a spatial constellation in contrast to the signaling constellation. We investigate the symbol error rate (SER) of the PSM scheme to strike a fine tradeoff between the signaling and the spatial constellation, i.e., the signaling-spatial constellation tradeoff, which minimizes the system's SER. First, we formulate the SER of the PSM scheme. Then, an explicit upper bound on the SER is determined based on an approximation using a weighted sum of exponentials. By minimizing the SER upper bound, we show that for phase-shift keying modulation, it achieves a sufficiently good tradeoff when the size of the signaling constellation is 4, i.e., the quadrature phase-shift keying. The numerical results show that the signaling-spatial constellation tradeoff determined by the derived SER upper bound significantly outperforms other PSM schemes with equal spectral efficiency. [ABSTRACT FROM AUTHOR]

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

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

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

Providing femto access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smartphones to the so-called femto-cloud. Such offloading promises to be beneficial in terms of battery savings at the mobile terminal (MT) and/or in latency reduction in the execution of applications. However, for this promise to become a reality, the energy and/or the time required for the communication process must be compensated by the energy and/or the time savings that result from the remote computation at the FAPs. For this problem, we provide in this paper a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency. Multiple antennas are assumed to be available at the MT and the serving FAP. As a result of the optimization, the optimal communication strategy (e.g., transmission power, rate, and precoder) is obtained, as well as the optimal distribution of the computational load between the handset and the serving FAP. This paper also establishes the conditions under which total or no offloading is optimal, determines which is the minimum affordable latency in the execution of the application, and analyzes, as a particular case, the minimization of the total consumed energy without latency constraints. [ABSTRACT FROM PUBLISHER]

This paper addresses energy-efficient power control for time-division-duplexing (TDD) multiple-input–single-output (MISO) systems. Assuming ideal channel reciprocity, the beamforming at the transmitter (TX) is based on the estimated channel state information (CSI) obtained from the pilot signal of the receiver (RX). We define the energy efficiencies of the TX and the RX separately and study their energy efficiency region. In addition, we seek a power control scheme that can achieve all the points on the Pareto boundary of the energy efficiency region. We propose to maximize the weighted system energy efficiency, which is the data rate divided by the weighted sum of the power consumption at the TX and the RX. A method based on the quasi-concavity of the weighted system energy efficiency is developed to solve the problem. Simulation results show that the proposed power control can achieve all the points on the Pareto boundary of the energy-efficiency region by varying the weight. [ABSTRACT FROM PUBLISHER]

High-speed and low-latency communications are one of the major requirements for connected vehicle environments. Safety messages in vehicular networks must arrive on time for each vehicle, and the optimization of driving paths also strongly depends on low-latency traffic information. To comply with the demands, a base station take important roles to provide a short service delay for the vehicles, even at the expense of performance. The relationship between delay time and decoding performance at receiver sides in physical layers can be explained by the performance/complexity tradeoff as follows. To achieve better performance in terms of the minimization of word error rates in decoding, the receiver usually requires higher complexity, which results in larger delays. We analyze this tradeoff based on the receiver queue model. This paper proposes a novel algorithm to adaptively select one of receiver candidates under the constraint of queue stability so as not to degrade low-latency communications. Based on the configurable architecture for multi-input multioutput (MIMO) detectors, this paper shows that the proposed algorithm works well on adaptive MIMO detector selection. [ABSTRACT FROM PUBLISHER]

Multiple-input multiple-output (MIMO) spatial multiplexing and beamforming are regarded as key technology enablers for the fifth-generation (5G) millimeter wave (mmWave) mobile radio services. Spatial multiplexing requires sufficiently separated and incoherent antenna array elements, while in the case of beamforming, the antenna array elements need to be coherent and closely spaced. Extensive 28-, 60-, and 73-GHz ultra-wideband propagation measurements in cities of New York City and Austin have indicated formation of two or more spatial lobes for the angles-of-departure and angles-of-arrival even for line-of-sight (LOS) transmission, which is an advantageous feature of mmWave channels, indicating that the transmitting and receiving array antenna elements can be co-located, thus enabling a single architecture for both spatial multiplexing and beamforming. In this paper, a two-level beamforming architecture for uniform linear arrays is proposed that leverages the formation of these spatial lobes. The antenna array is composed of sub-arrays, and the impact of sub-array spacing on the spectral efficiency is investigated through simulations using a channel simulator named NYUSIM developed based on extensive measured data at mmWave frequencies. Simulation results indicate spectral efficiencies of 18.5–28.1 bits/s/Hz with a sub-array spacing of 16 wavelengths for an outdoor mmWave urban LOS channel. The spectral efficiencies obtained are for single-user (SU) MIMO transmission at the recently allocated 5G carrier frequencies in July 2016. The method and results in this paper are useful for designing antenna array architectures for 5G wireless systems. [ABSTRACT FROM PUBLISHER]

As the conventional spatial modulation (SM) system lacks an efficient downlink multiple access scheme, this paper proposes a novel downlink nonorthogonal multiple access aided multiple-input multiple-output SM system with finite alphabet inputs. Mutual information (MI) is used to characterize the system's achievable spectral efficiency (SE). Because the MI lacks a closed-form formulation, in this paper we propose a computational-efficient lower bound to provide an approximation to the simulated MI. Besides, preprocessing is also designed at the receiver to mitigate the detrimental effect of channel correlation, which leads to striking a higher SE performance. Simulation results not only confirm the accuracy of our SE analysis, but also substantiate the superior SE performance achieved by the proposed preprocessing. [ABSTRACT FROM PUBLISHER]

In the existing millimeter-wave (mmWave) wireless positioning systems, the method based on sparse Bayesian learning (SBL) uses the channel sparsity to estimate the parameters required for positioning, such as angle of arrival (AOA) and time delay, but most existing SBL solutions only consider the angle sparsity. In this paper, we consider the joint sparsity of the angle domain and time delay domain to propose an improved SBL algorithm by using a new two-dimensional adaptive grid refinement method in the SBL framework. This algorithm solves the grid mismatch problem caused by the fixed grid in the traditional SBL method, and reduces the algorithm complexity of the off-grid SBL (OGSBL) algorithm. We also obtain the Cramér-Rao bound (CRB) of AOA, time delay and position estimation based on the mmWave multipath signals to analyze the estimation errors. Simulation results show that the performance of the proposed algorithm is better than existing algorithms and can approach CRB. [ABSTRACT FROM AUTHOR]

Multiple-input-multiple-output (MIMO) systems significantly increase the network throughput and coverage probability for short-packet communications. In this paper, a tight lower bound on the average achievable rate of MIMO short-packet communication systems is theoretically derived, considering flat uncorrelated Rayleigh fading MIMO channels. The derivations are based on the eigenvalue analysis of a Wishart matrix and Jensen's inequality. Given the actual transmission rate, a tight approximation on the average block error rate (BLER) of MIMO short-packet communication systems is also provided, which is based on the moment generating function and inverse Laplace transform. Numerical results demonstrate that both our theoretically derived analytical average achievable rate lower bound and approximate average BLER are almost the same as the simulation results. [ABSTRACT FROM AUTHOR]

Multiple remote antenna units (RAUs) cooperate to serve a certain user in cell-free distributed massive multiple-input multiple-output (MIMO) systems. Due to the different distances between each RAU and the user, asynchronous reception effects will occur. This paper studies the impacts of asynchronous reception effects on cell-free distributed massive MIMO systems. We first derive the minimum-mean-square error (MMSE) channel estimation under the asynchronous reception effects. Given the estimated channel state information, we derive the closed-form expressions of the user achievable rates with maximum ratio transmission (MRT) and regularized zero-forcing (RZF) precoders, which are further used to analyze the impacts of asynchronous reception effects. The accuracy of the closed-form expressions are verified. Simulation results demonstrate that asynchronous reception effects cause a non-negligible drop on the system spectral efficiency. Moreover, the performance degradation is proportional to the subcarrier sequence number and even more serious with the increasing of signal-to-noise ratio (SNR) or the number of antennas per RAU. [ABSTRACT FROM AUTHOR]

In this paper, we investigate hybrid beamforming, user scheduling, and resource allocation optimization based on spectrum coexisting forward transmission in integrated terrestrial-satellite network (ITSN) with the purpose of improving system sum rate and energy efficiency. Considering the limitation of on-board beamforming, a hybrid analog-digital beamforming scheme is designed under the scenario of millimeter wave (mmWave) coexisting in the ITSN framework. Besides, in order to further mitigate intra-beam and inter-beam interference, we propose an adaptive user scheduling scheme, which first determines the cluster center based on adaptive threshold, and then selects users with less channel correlation into a scheduling cluster. Moreover, we model system sum rate maximization problem that incorporates maximum power constrains and minimum data rate requirements. Combined with the aforementioned hybrid beamforming and user scheduling strategy, we formulate the sum rate maximizing problem to a pure power allocation issue. In view of the non-convexity and high complexity, we propose a feasible optimization method based on the minimum mean square error (MMSE) criterion and logarithmic linearization to optimize the power allocation for each user terminal (UT). Simulation results show that our proposed joint beamforming and resource allocation optimization scheduling scheme can achieve an attractive gain in system sum rate and energy efficiency compared with conservative beamforming and allocations. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of decoding in large-scale multiple-input–multiple-output (MIMO) systems. In this case, the optimal maximum-likelihood (ML) detector becomes impractical due to an exponential increase in the complexity with the signal and the constellation dimensions. This paper introduces an iterative decoding strategy with a tolerable complexity order. We consider a MIMO system with finite constellation and model it as a system with sparse signal sources. We propose an ML relaxed detector that minimizes the Euclidean distance with the received signal while preserving a constant \ell1 -norm of the decoded signal. We also show that the detection problem is equivalent to a convex optimization problem, which is solvable in polynomial time. Two applications are proposed, and simulation results illustrate the efficiency of the proposed detector. [ABSTRACT FROM PUBLISHER]

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

An iterative detection and decoding (IDD) technique has recently received much attention due to its capacity approaching performance and manageable complexity for (parallel) turbo-coded systems. The existing IDD receivers process indiscriminately the a priori information of the systematic bits and the parity bits generated by the turbo decoder in the front-end detection. In this paper, we first show that the parity bits of the parallel turbo codes are inherently less protected than the systematic bits, which leads to suboptimality for the IDD receivers. Based on this observation, we then propose an unequal-error-correcting-capability-aware technique to mitigate the associated performance loss. As an illustrative example, the minimum-mean-square-error (MMSE) filtering and soft interference cancelation (MMSE-SIC)-aided iterative receiver for parallel-turbo-coded multiple-input–multiple-output (MIMO) systems is employed in this paper. Numerical results manifest that the MMSE-SIC-aided iterative receiver based on the proposed paradigm achieves noticeable performance gains over the conventional unequal-error-correcting-capability-agnostic one even with reduced computational complexity. The extension of the proposed principle to other iterative algorithms for parallel-turbo-coded data transmission is straightforward. [ABSTRACT FROM PUBLISHER]

This paper addresses energy efficiency (EE) optimization problems for uplink multiuser multiple-input–multiple-output (MIMO) systems with zero-forcing (ZF) transceivers, subject to a joint power and rate constraint for each user. As the optimization problem considered in this paper is quite different from the traditional one, directly applying the Dinkelbach method to the new EE optimization problem cannot bring an advantage of low complexity. Hence, we try to propose a novel approach inspired by the homotopy algorithms, where we concentrate our attention on the solution path for the EE optimization. Making use of the piecewise-defined property between power allocations and the overall transmission power, we fit the entire path of solution for every value of the overall transmission power by replacing the search variable with a specially selected parameter. By checking only a finite number of breakpoints, we then try to propose a new homotopy-type algorithm to obtain the maximum EE in an exact closed form to reduce the computational complexity significantly. Simulation results verify the performance of the new method. [ABSTRACT FROM PUBLISHER]

Multiple-input–multiple-output (MIMO) technology can efficiently use the spectrum to increase the communication throughput. Designing low-complexity detection algorithms with high performance for the MIMO system has been an important issue. In this paper, we propose efficient detection algorithms for MIMO systems based on differential metrics. We first define differential metrics and give their recursive calculation of different orders. Based on differential metrics, we give the principle of gradient search. We then propose a gradient search algorithm (GSA) that can provide a tradeoff between performance and complexity. The GSA applies the indicative functions such that we can determine in advance some maximum-likelihood (ML) bits of the initial sequence and reduce the searching range. The GSA also uses a stop condition with which we can stop the search if the proper condition is satisfied. The GSA does not need QR decomposition (QRD) or matrix inversion. The multiplicative operations are only necessary before the searching process, during which only the additive operations are needed. For large-scaled MIMO systems, we also give a simple searching algorithm based on differential metrics. Finally, we propose a fixed-complexity gradient algorithm (FCGA), which has a fixed number of operations during the searching process and is appropriate for pipelined hardware implementation. The simulation results validate the efficiency of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

This paper investigates the secrecy outage performance of transmit antenna selection (TAS)/maximal ratio combining (MRC) in multiple-input–multiple-output (MIMO) cognitive radio networks (CRNs) over Rayleigh fading channels. In the considered system, a secondary user (SU-TX) equipped with NA (NA\geq \text{1}) antennas uses TAS to transmit confidential messages to another secondary user (SU-RX), which is equipped with NB (NB\geq \text{1}) antennas and adopts the MRC scheme to process multiple received signals. Meanwhile, an eavesdropper equipped with NE (NE\geq \text{1}) antennas also adopts the MRC scheme to overhear the transmitted information between SU-TX and SU-RX. SU-TX adopts the underlay strategy to guarantee the quality of service (QoS) of the primary user (PU) without spectrum sensing. In this paper, we derive the exact and asymptotic closed-form expressions for the secrecy outage probability (SOP). Simulations are conducted to validate the accuracy of the analysis. [ABSTRACT FROM PUBLISHER]

This paper investigates the issues on optimal antenna deployment at a base station to maximize downlink ergodic sum-rate capacity. We analyze the ergodic sum-rate capacity of a multiuser multiple-input–multiple-output (MIMO) system using random matrix theory, and the analysis reveals that such a capacity depends largely on the deployed antenna structure. Moreover, we have found an optimal antenna configuration based on the proposed particle swarm optimization (PSO) algorithm to maximize the ergodic sum-rate capacity. The theoretical results on downlink ergodic sum-rate capacity match simulation results very well, validating the accuracy of the theoretical analysis. The simulation results show that the proposed optimal antenna configuration offers the largest downlink sum-rate capacity with the best bit error rate (BER) performance compared with uniform linear arrays (ULAs) and uniform circular arrays (UCAs). It is concluded that the optimal antenna coordinates can be predetermined before deploying the antennas in a given base station. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problem of securing information transmission in very adverse environments, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate channel CSI, by introducing a massive multiple-input–multiple-output (M-MIMO) relay. The relay is powered through wireless power transfer from the source, such that it can flexibly adjust its position according to the secrecy requirement. The benefits of a M-MIMO relay are fully exploited to enhance both power transfer efficiency and information transmission security. In particular, the challenging issues incurred by short interception distance and long transfer distance are well addressed simultaneously. The focus of this paper is on investigating the secrecy performance of two classical relaying protocols, namely amplify-and-forward (AF) and decode-and-forward (DF), and obtaining explicit expressions of secrecy outage capacity in terms of transmit power, channel condition, and antenna number. Furthermore, we propose two effective performance optimization schemes, i.e., power control at the source, and relaying protocol switch at the relay. Finally, our theoretical claims are validated by simulation results. [ABSTRACT FROM PUBLISHER]