Multiuser Multiuser Multiple-input Multiple-output Systems Research Articles

Statistically Robust Transceiver Design for Multi-RIS Assisted Multi-User MIMO Systems

In this letter, we investigate the robust transceiver design for a downlink multi-user multiple-input multiple-output (MIMO) system assisted by multiple reconfigurable intelligent surfaces (RISs), where the base station (BS) and multiple users are all equipped with multiple antennas. Different from most previous RIS related works focusing on worst-case performance optimization, which may lead to overly conservative transceiver designs, we assume stochastic channel estimation errors for the considered system, and aim to minimize the average sum mean square error (MSE) of the considered system by jointly optimizing the transmit precoders, the receive equalizers, and the RIS reflecting coefficients. To address the non-convexity of the formulated problem induced by strongly coupled optimization variables, we develop a low-complexity alternating optimization (AO) algorithm to find a locally optimal solution, where the unique optimal solution to each subproblem can be derived in closed-form. Numerical simulations demonstrate the robustness and excellent average sum MSE performance of the proposed AO algorithm compared to the adopted benchmark scheme.

Deep learning-based transceiver design for multi-user MIMO systems

Multi-user multiple-input multiple-output (MIMO) is a key technique to increase both the channel capacity and the number of users that can be served simultaneously. One of the main challenges related to the deployment of such systems is the complexity of the transceiver processing. Although the conventional optimization algorithms are able to provide excellent performance, they generally require considerable computational complexity, which gets in the way of their practical application in real-time systems. In contrast to existing work, we study a DL-based transceiver design scheme for a downlink MIMO broadcasting channel (MIMO BC) system, which consists of a base station (BS) serving multi-users. The objective of this work is to maximize the sum-rate of all users by jointly optimizing the transmitter and receivers under the total power constraint, while suppressing interference as much as possible. Due to the inter-user interference in such system, the considered problem is nonconvex and NP-hard. Different from traditional optimization algorithms, we rely on the convolutional neural networks (CNNs) to optimize the transceivers in an adaptive way. In the proposed scheme, we develop an unsupervised learning strategy, where a loss function is constructed innovatively for reducing the inter-user interference. Simulation results show that the inter-user interference is reduced effectively by our proposed CNN-based transceiver optimization method.

Secrecy Throughput in Full-Duplex Multiuser MIMO Short-Packet Communications

In this letter, we consider the physical-layer security (PLS) in full-duplex (FD) multiuser multiple-input-multiple-output (MIMO) short-packet communications, where a base station (BS) transmits precoded signals for secure downlink multicast while receiving signals from uplink users. To quantify the PLS performance in the worst-case scenario, we consider the possible maximum wiretapping capability of a multi-antenna eavesdropper. Taking into account the self-interference (SI) in FD mode and the co-channel interference (CCI) from uplink to downlink, we analyst the secrecy throughput in finite blocklength regime and obtain its analytic expression, which perfectly matches asymptotic and simulation results in various scenarios. Moreover, the investigations on secrecy throughput substantiate that the FD multiuser MIMO systems outperform their half-duplex counterparts given the SI being sufficiently suppressed and the CCI being well managed.

Linear Precoding and Stream Combining for Rate Splitting in Multiuser MIMO Systems

This letter develops practical linear precoding and stream combining techniques for rate-splitting (RS) in multiuser multiple-input multiple-output (MIMO) systems. We propose linear combining techniques based on the Min-Max, the maximum ratio and the minimum mean-square error criteria along with Regularized Block Diagonalization (RBD) precoders for RS-based multiuser multiple-antenna systems. An analysis of the sum rate performance is carried out, leading to closed-form expressions. Simulations show that the proposed combining schemes offer a significant sum rate performance gain over conventional linear precoding schemes.

Multi-Objective Power Minimization Design for Energy Efficiency in Multicell Multiuser MIMO Beamforming System

In this study, we propose a multi-objective power optimization design in a multicell multiuser multiple-input multiple-output (MIMO) beamforming system in the future era of green communications for energy efficiency. First, we consider a multicell multiuser MIMO system with multiple base stations (BSs) and each BS could serve multiple downlink mobile stations (MSs) simultaneously. Second, we formulate a multi-objective optimization problem (MOP) to simultaneously minimize the downlink powers of different groups of cells subject to the signal to interference plus noise ratio (SINR) constraints. An indirect method is proposed to transform the MOP of multi-objective power minimization design of multicell multiuser MIMO beamforming system to a semidefinite programming (SDP)-constrained MOP. In order to efficiently solve the multi-objective power minimization problem with a low computational complexity, a novel multi-objective evolutionary algorithm (MOEA) with modification is proposed to guarantee the global convergence of Pareto optimal solutions. Finally, simulation results are provided to validate the performance and show the superiority of the proposed multi-objective beamforming green design to minimize the downlink power consumption of MIMO beamforming system in different groups of cells simultaneously.

Accurate Performance Analysis of Coded Large-Scale Multiuser MIMO Systems with MMSE Receivers

In this paper, we estimate the uplink performance of large-scale multi-user multiple-input multiple-output (MIMO) networks. By applying minimum-mean-square-error (MMSE) detection, a novel statistical distribution of the signal-to-interference-plus-noise ratio (SINR) for any user is derived, for path loss, shadowing and Rayleigh fading. Suppose that the channel state information is perfectly known at the base station. Then, we derive the analytical expressions for the pairwise error probability (PEP) of the massive multiuser MMSE–MIMO systems, based on which we further obtain the upper bound of the bit error rate (BER). The analytical results are validated successfully through simulations for all cases.

A Novel Nonlinear and Non-iterative Precoding Technique for Single and Multi User MIMO Systems

A modification of the well known linear and iterative based precoder intended for both single and multi-user multiple-input multiple-output (MIMO) has been proposed. The proposed precoder uses the nonlinear and non-iterative processing strategies to obtain more efficient and less complexity designs. The non-linearity in the precoder is introduced by using the nonlinear constellation precoding technique based on maximum distance separable codes. Also, the computation complexity in iterative based precoder design is avoided by using a singular value decomposition method. The maximum likelihood detection for the linear MIMO channel is considered. The simulation results are provided in-terms of bit error rate versus signal-to-noise ratio to show that the proposed combined non-linear and non-iterative precoding schemes outperform the conventional linear and iterative based MIMO precoder designs.

Fundamental Limits of Training-Based Uplink Multiuser MIMO Systems

In this paper, we endeavor to seek a fundamental understanding of the throughput limit for a training-based uplink multiuser multiple-input multiple-output (MIMO) system. In a multiuser MIMO system, users are geographically separated and experience significantly different large-scale fading. As large-scale fading varies order of magnitude more slowly than small-scale fading, the system resource consumed for acquiring large-scale fading coefficients is usually marginal as compared with that for small-scale fading coefficients. Such a difference between large-scale and small-scale fadings, however, has not been appropriately handled in the existing approaches for training-based multiuser MIMO systems. In this paper, we ignore the overhead for large-scale fading acquisition by assuming that the large-scale fading coefficients are known a priori , whereas the small-scale fading coefficients are estimated via training. Our target is to maximize the mutual information lower bound (MILB) of a training-based uplink multiuser MIMO system over various system parameters, including the training length, the training signals, the number of users, and the power allocation between training and data transmission. As the exact solution is difficult, we establish upper and lower bounds of the MILB. Specifically, we use the majorization theory to establish an upper bound of MILB. We then propose a lower bound of the MILB by deactivating a portion of users with the smallest large-scale fading gains and assigning orthogonal training sequences to the rest of the users. We show that this simple lower bound is asymptotically optimal for MILB maximization in the high signal-to-noise ratio (SNR) regime. We also show that the upper and lower bounds are reasonably tight in the finite SNR regime under various system configurations. Furthermore, we derive the optimal training design for MILB maximization in uplink multiuser MIMO with uniform large-scale fading. Numerical results are presented to verify our analysis.

Exploiting high rate differential algebraic space‐time block code in downlink multiuser MIMO systems

This paper considers a multiuser multiple-input multiple-output (MIMO) space-time block coded system that operates at a high data rate with full diversity. In particular, they propose to use a full rate downlink algebraic transmission scheme combined with a differential space-time scheme for multiuser MIMO systems. To achieve this, perfect algebraic space-time codes and Cayley differential transforms are employed. Since channel state information (CSI) is not needed at the differential receiver, differential schemes are ideal for multiuser systems to shift the complexity from the receivers to the transmitter, thus simplifying user equipment. Furthermore, orthogonal spreading matrices are employed at the transmitter to separate the data streams of different users and enable simple single user decoding. In the orthogonal spreading scheme, the transmitter does not require any knowledge of the CSI to separate the data streams of multiple users; this results in a system which does not need CSI at either end. With this system, to limit the number of possible codewords, a sphere decoder is used to decode the signals at the receiving end. The proposed scheme yields low complexity transceivers while providing full rate full diversity with good performance. Simulation results demonstrate the effectiveness of the proposed scheme.

Mitigation of self‐interference and multi‐user interference in downlink multi‐user MIMO system

Here, the authors develop a method of simultaneous optimisation of precoder and equaliser for the multi-user multiple-input multiple-output (MIMO) system by minimising outage probability. In order to do that, the authors first characterise the signal-to-interference-plus-noise ratio of downlink multi-user MIMO system in the presence of both multi-user interference and self-interference. The closed-form expression for the outage probability is derived in terms of the eigenvalues of an indefinite weight matrix of a quadratic norm. Next, the authors develop an active-set algorithm-based precoder and equaliser by minimising the derived outage probability expression. This work investigates the effect of various system parameters such as the number of users, the number of multi-path channels, the number of transmitting and receiving antenna elements, and the additive noise variance on the outage probability and bit error rate. Simulation results validate the theoretical analysis for multiple system configurations. Lastly, the authors show that the designed precoder and equaliser improves the overall system performance.

Sum-Rate Analysis for Multi-User MIMO Systems With User Exposure Constraints

Fifth generation (5G) and beyond cellular systems are expected to support multiple uplink transmit antennas. Previous research demonstrates that designing waveforms satisfying near field user exposure constraints affects the far-field data rates achievable by portable devices using multiple transmit antennas. Therefore, user exposure constraints need to be taken into account in the uplink transmission covariance matrix design (e.g., precoder design) for 5G. Specific absorption rate (SAR) is a widely accepted user exposure measurement used in wireless communication regulations throughout the world. In this paper, we perform sum-rate analysis for a multi-user multiple-input multiple-output (MIMO) system with SAR constraints enforced at each user. The maximum achievable sum rates for various channel state information at the transmitter scenarios are studied in this paper. The SAR-aware MIMO transmission methods are based on the modified waterfilling algorithm. Simulation results show our proposed methods outperform the conventional transmission strategy for the two user case.

Spectral and energy efficiency of downlink MU-MIMO systems with MRT

This paper studies the achievable spectral efficiency (SE) of downlink multiuser multiple-input-multiple-output (MIMO) system, where the base station (BS) is deployed an arbitrary finite antenna number and communicates simultaneously with many users. We assume that the BS has accurate channel state information (CSI) and adopt maximum ratio transmission (MRT) precoding. An accurate analytical result for the achievable SE is obtained. Based on the analytical result on the achievable SE, we further study the achievable energy efficiency (EE) of multiuser MIMO system by considering an energy consumption model. Results indicate that the increasing number of BS antennas can boost the achievable SE of system, whilst the achievable SE tends to a saturated rate in the high signal-to-noise ratios (SNR) regime. Furthermore, an important conclusion is that the increasing number of users is beneficial for the achievable EE and there is an optimal antenna number to maximize the EE of system.

Non-Orthogonal Multiple Access (NOMA) for Downlink Multiuser MIMO Systems: User Clustering, Beamforming, and Power Allocation

We investigate the application of non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in downlink multiuser multiple-input multiple-output (MIMO) cellular systems, where the total number of receive antennas at user equipment (UE) ends in a cell is more than the number of transmit antennas at the base station (BS). We first dynamically group the UE receive antennas into a number of clusters equal to or more than the number of BS transmit antennas. A single beamforming vector is then shared by all the receive antennas in a cluster. We propose a linear beamforming technique in which all the receive antennas can significantly cancel the inter-cluster interference. On the other hand, the receive antennas in each cluster are scheduled on the power domain NOMA basis with SIC at the receiver ends. For inter-cluster and intra-cluster power allocation, we provide dynamic power allocation solutions with an objective to maximizing the overall cell capacity. An extensive performance evaluation is carried out for the proposed MIMO-NOMA system and the results are compared with those for conventional orthogonal multiple access (OMA)-based MIMO systems and other existing MIMO-NOMA solutions. The numerical results quantify the capacity gain of the proposed MIMO-NOMA model over MIMO-OMA and other existing MIMO-NOMA solutions.

Partly random multiple weighting matrices selection for orthogonal random beamforming

In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

Low-Complexity Precoding Design for Massive Multiuser MIMO Systems Using Approximate Message Passing

A practical challenge in the precoding design of massive multiuser multiple-input multiple-output (MIMO) systems is to facilitate hardware-friendly implementation. To achieve this, we propose a low peak-to-average power ratio (PAPR) precoding based on an approximate message passing (AMP) algorithm to minimize multiuser interference (MUI) in massive multiuser MIMO systems. The proposed approach exhibits fast convergence and low complexity characteristics. Compared with a conventional constant-envelope precoding and an annulus-constrained precoding, simulation results demonstrate that the proposed AMP precoding is superior both in terms of computational complexity and average running time. In addition, the proposed AMP precoding exhibits a much desirable tradeoff between MUI suppression and PAPR reduction. These findings indicate that the proposed AMP precoding is a suitable candidate for hardware implementation, which is very appealing for massive MIMO systems.

Secrecy capacity and outage probability of multiuser MIMO systems with zero forcing receivers

In this paper, we evaluate the secrecy performance of the zero forcing receiver operating in the multiuser multiple-input multiple-output (MIMO) system with user scheduling. We first derive the exact closed form expressions for the probability of non-zero secrecy capacity (PNZSC). We consider Rayleigh fading with non-identical fading parameters of the eavesdropper’s channel. We further derive the secrecy outage probability (SOP) which accurately reveals the secrecy diversity order and the secrecy array gain. Numerical results shows that our system is valid and accurate for any number of transmitter, receiver and eavesdropper antennas.

Joint Optimization of Power and Data Transfer in Multiuser MIMO Systems

We present an approach to solve the nonconvex optimization problem that arises when designing the transmit covariance matrices in multiuser multiple-input multiple-output (MIMO) broadcast networks implementing simultaneous wireless information and power transfer (SWIPT). The MIMO SWIPT problem is formulated as a general multiobjective optimization problem, in which data rates and harvested powers are optimized simultaneously. Two different approaches are applied to reformulate the (nonconvex) multiobjective problem. In the first approach, the transmitter can control the specific amount of power to be harvested by power transfer whereas in the second approach the transmitter can only control the proportion of power to be harvested among the different harvesting users. We solve the resulting formulations using the majorization–minimization (MM) approach. The solution obtained from the MM approach is compared to the classical block-diagonalization (BD) strategy, typically used to solve the nonconvex multiuser MIMO network by forcing no interference among users. Simulation results show that the proposed approach improves over the BD approach both the system sum rate and the power harvested by users. Additionally, the computational times needed for convergence of the proposed methods are much lower than the ones required for classical gradient-based approaches.

On the Impacts of Composite Fading on Large-Scale Multi-User MIMO Systems

This letter considers the uplink of a large-scale multi-user multiple-input-multiple-output (MIMO) system where multiple single antenna terminals transmit simultaneously to an array of hundreds of antennas. The base station (BS) is assumed to have perfect channel state information (CSI). Under Rayleigh fading and lognormal shadowing, the probability density function (PDF) of the received signal-to-interference-plus-noise-ratio (SINR) is approximated by a lognormal distribution for different receiver types and closed-form expressions for the outage probability are presented. The effects of shadowing on the performance of the system are quantified.

Energy-Efficient Adaptation of Pilot Power, Data Power, and Transmission Rate for Downlink Multiuser MIMO Systems

This paper addresses energy-efficient link adaptation for downlink multiuser multiple-input-multiple-output (MIMO) systems. Different from the previous works on energy efficient MIMO techniques, we take into account finite pilot power and the corresponding effect of imperfect channel state information (CSI) at the users. We analyze the average throughput and define the energy efficiency (EE) of downlink multiuser MIMO systems. We show that the EE of the system is not jointly quasi-concave with respect to pilot power, data power, and transmission rate. For this reason, we propose an efficient algorithm that alternately updates pilot power, data power, and transmission rate to improve the EE of the system. Simulation results show that the proposed scheme significantly enhances the EE, and the resulting EE is comparable to the maximal EE obtained by the exhaustive search.

Feed back load analysis for broadcast channels with zero‐forcing beamforming

Multiuser multiple-input–multiple-output (MIMO) has great potential to substantially improve throughput of wireless networks. Unfortunately, it requires a significant amount of feed back for user selection, which prevents practical implementation. The authors propose a feed back reduced downlink multiuser MIMO system, where a signal-to-interference-plus-noise ratio (SINR) threshold is carefully designed. Only the users whose SINRs are above the threshold feed back their SINRs and channel direction information (CDI) to the base station. They establish a monotonic relation between the threshold and the average feed back overhead. Based on the established relation, they design the threshold that balances the tradeoff between the feed back load and the sum rate. Simulation results show that the proposed approach can achieve the same performance as the conventional full-feed back scheme (where every user feeds back its SINR and CDI), while the proposed approach is able to reduce the system overhead by more than 40%.