Multiuser Multiple-input Multiple-output Communication Research Articles

Asymptotic performance of reconfigurable intelligent surface assisted MIMO communication for large systems using random matrix theory

AbstractReconfigurable intelligent surface (RIS) can provide unprecedented spectral efficiency gains and excellent ability to manipulate electromagnetic waves. This article considered a RIS‐assisted multiuser multiple‐input multiple‐output (MIMO) downlink system, where the beamforming at the base station and RIS are jointly designed to maximize the sum‐rate. For the large dimension scenario and high‐rank beamforming matrix, the accurate deterministic approximations from random matrix theory are then utilized to simplify the RIS‐assisted MIMO systems. The asymptotical signal‐to‐interference‐plus‐noise ratio values obtained through random matrix theory is infinitely close to the theoretical limits calculated by accurately iteration. And the performance of the proposed algorithm computed via the sharing second‐order channel statistics matches that of the RIS algorithm with sharing full channel state information asymptotically. The deterministic approximations are instrumental to get improvement into the structure of the optimal beamforming and to reduce the implementation complexity in large‐scale MIMO system. Numerical simulations results are provided to evaluate and verify the accuracy of the asymptotic results obtained from the proposed algorithm in the finite system regime. With the complex operation process of large dimension matrix reducing to the deterministic approximations, a lower computational complexity can be obtained compared with other methods.

Design and Performance Analysis of the Dynamic Reduction of Intrinsic Interference Suppression and BER using QAM-based FBMC for MU-MIMO Communications

The present research work is focused on the study of co-channel interface with its minimization techniques without influencing its performance, in turn, which is desired to achieve the minimized complexity of Quadrature Amplitude Modulation (QAM)-based Filter Bank Multi-Carrier (FBMC) to minimize the interference and increase the spectral features with consideration of intrinsic features extractions for the ML (Maximum Likelihood) synthesis systems. The valid measures are given various concerns under consideration, to start with the consideration of the evaluation of the Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFD performance metrics along with the FBMC/QAM in signal transmission in a dedicated fading channel for the evaluation of the modulation order and BER as a required trade-off for quality assessments. From the results, it can be noted that the proposed FBMC QAM has performed better when compared with conventional FBMC systems. The present research also includes considering and calculating the efficiency of nonlinear channels with the Multi-User Multiple Input Multiple Output (MU-MIMO) and FBMC/QAM techniques. In continuation, the obtained results are dominating significantly to access the possible solution to meet the efficiency of the proposed system. In the next part of the research, it is considered with implementation of the sub-detector during the downlink of the system with the technique of threshold-driven strategy for better accuracy and minimization of the complexity in terms of ML detection in terms of order of its modulation. The calculations of the proposed technique with better BER are done on the recent MATLAB platform with its simulation demonstration for its detailed observation.

Codesign for Hybrid MU-MIMO Communication and MIMO Radar Systems Based on Mutual Information

To enhance the coexistence performance of multiple-input multiple-output (MIMO) radar system and multiuser MIMO communication system with hybrid beamforming architecture, this work proposes a codesign problem regarding the digital and analog beamformers of communication base station, the receive beamformers of downlink users, and the transmit waveform of radar. An information-theoretic criterion is adopted to improve the radar detection performance, while the signal-to-interference-plus-noise ratio requirement is imposed on each downlink user to ensure communication quality. In addition, similarity restriction is also involved to manage some significant radar waveform characteristics. An iterative algorithm is introduced to tackle the resulted nonconvex and NP-hard problem. In each iteration, several subproblems are developed to decompose the original problem and are solved by the lower bound maximization and the alternating direction method of multiplier algorithm. Numerical simulations show that the proposed algorithm allows the objective function to increase monotonically and finally converge to a finite value. It also shows that the codesign scheme can effectively optimize the radar detection performance while ensuring the achievable sum rate and the bit error rate of the communication system.

Fair Licensed Spectrum Sharing Between Two MNOs Using Resource Optimization in Multi-Cell Multi-User MIMO Networks

Licensed spectrum sharing has been a promised approach to provide mobile network operators (MNOs) with required spectrum at times of increased traffic, or to improve the mobile user data rate with limited spectral resources. In this paper, we investigate the use of multi-user multiple-input, multiple-output (MIMO) techniques to enable licensed spectrum sharing. Specifically, we present a fair spectrum sharing system between two MNOs in multi-cell multi-user MIMO networks. We impose fairness by ensuring that each MNO receives spectrum in proportion to the amount it contributes. We formulate a constrained optimization problem to determine resource allocation and user scheduling across two MNOs. Since the problem is non-convex, we develop an algorithm to provide an effective solution through fractional programming and block coordinate descent. Our numerical results illustrate that the proposed spectrum sharing scheme can achieve up to 60 % improvement in terms of the average user rate among the two operators while ensuring that neither MNO is exploited for participating in the sharing mechanism. This improvement is in relation to the baseline of each MNO using multi-user MIMO communications on its own. In addition, most users, especially cell-center users close to the BSs, take advantage of our proposed spectrum sharing framework.

DM-COM: Combining Device-to-Device and MU-MIMO Communications for Cellular Networks

In cellular networks, multiuser multiple-input multiple-output (MU-MIMO) is a key technology and has already been deployed in many real systems. Recently, device-to-device (D2D) communication has emerged as another promising technology as it offers several advantages, such as traffic offloading, low-latency transmissions, and enhanced spectral efficiency. Although there are many results of these two technologies, most of them are limited to their respective domains and there is a lack of practical design to combine both technologies for cellular networks. In this article, we present DM-COM, a practical scheme for enabling the coexistence of D2D and MU-MIMO subsystems in cellular networks. The enabler of DM-COM is a new approach for managing the mutual interference between the two subsystems, which does not require channel state information and is, therefore, amenable to practical implementation. We have built a prototype of DM-COM on a wireless testbed and evaluated its performance in a real-world wireless environment. Our experimental results show that, using DM-COM in a small cellular network, D2D users achieve 1.9 bit/s/Hz spectral efficiency, while MU-MIMO users have less than 8% throughput degradation compared to the case without D2D users.

Interference Utilization for Spectrum Sharing Radar-Communication Systems

This paper proposes a new transmitter precoding approach for co-existence between multiple-input multiple-output (MIMO) radar and multi-user MIMO communication systems employing phase shift keying (PSK) modulation. To enable the satisfactions of radar communication functionalities, the common practice is to suppress the mutual interferences, while our proposed scheme is to use the known interferences existing already in radar and communications systems and make the most of them: selectively reverse the destructive interferences to the negative direction while retaining the interferences which are beneficial to the desired signal. The resulting interferences are always kept constructive and can contribute to the power of the useful signal. Numerical results validate that the effective signal to noise ratio (SNR) can be enhanced by 7 dB with no additional power-peruser investment.

Spatial Constellation Design-Based Generalized Space Shift Keying for Physical Layer Security of Multi-User MIMO Communication Systems

We propose a novel spatial constellation design (SCD) method with generalized space shift keying (GSSK-SCD) signaling for physical layer security (PLS) in multi-user (MU) multiple-input multiple-output (MIMO) communication systems. In GSSK-SCD, the received spatial constellations are optimized through a novel precoding scheme, which minimizes the BERs at legitimate users and significantly worsens eavesdroppers' BER. In addition to extensive BER simulations, we also provide analytical expressions for the secrecy rate regions for the proposed GSSK-SCD. Both analytical derivations and simulation results, including comparisons with artificial noise aided conventional GSSK, reveal that the GSSK-SCD approach provides significant PLS improvements for MU-MIMO systems.

Mutual interference alignment for co-existing radar and communication systems

In this paper, we propose a mutual interference alignment (IA) method for interference elimination in co-existing multiple-input multiple-output (MIMO) radar and multi-user MIMO communication systems, namely, radar-communication systems. Traditional IA methods proposed for communication systems cannot be directly adopted in the radar-communications due to failure to fulfill the requirements of radar target detection. In contrast, our proposed mutual IA method can efficiently improve the signal-to-noise ratio (SNR) needed by radar functionalities without reducing the degrees-of-freedom (DoFs) of communication system, which implies no degradation for the communication performance. The algorithm idea is first to align all interferences at every receiver to one signal space, then the interferences can be easily canceled by receive filter. It is examined by the Neyman-Pearson (NP) test for radar functionality, while the communication performance is evaluated by DoFs and bit error rate (BER) analysis. Both theory analysis and numerical results are provided to validate the effectiveness of the proposed mutual IA method for co-existing radar and communication systems.

A Novel Downlink Interference Alignment Method for Multi-User MIMO System With No CSIT: A Space-Time Coding Approach

The problem of interference alignment in multi-user multiple-input multiple-output communication systems is considered, in this paper. A specific transmission strategy is proposed to transmit the symbols of multiple users which enables a significant saving of transmission time slots as compared to a trivial time division multiplexing based strategy. In order to detect the symbols at different receivers, the concept of left null of channel vector is utilized. The statistical properties of received signal-to-noise ratio at receiving end are studied by using probability density function, cumulative distribution function. Further, analytical performance of the system is discussed in terms of symbol error rate and diversity order by using moment generating function based approach. It is observed through theoretical analysis that the error performance of the proposed scheme degrades with increasing number of users; but this loss in performance can be compensated by deploying more antennas at the receivers. It is also shown through simulations that the computational complexity of the proposed scheme is also very much less as compared to the existing schemes.

Optimal 3-D Aerial Relay Placement for Multi-User MIMO Communications

In this paper, an airborne multi-user (MU) multiple-input multiple-output (MIMO) communication system is investigated, consisting of multiple users sources, multiple users destinations, and an aerial platform acting as a decode-and-forward (DF) relay. In this context, a novel three-dimensional (3-D) geometry-based optimization method for the relay location is proposed and expressions for the outage probability are presented. The results highlight the impact of the relay position, power allocation, fading severity, and number of antennas on the system performance.

Secure multiuser MIMO communication systems with imperfect channel state information

In this paper, we propose a secure wireless communications system through a multiple input multiple output (MIMO) channel which includes a multiple antenna base station and multiple single antenna legitimate users that are overheard by a multiple antenna eavesdropper. By assuming that the eavesdropper’s channel is unknown by the base station, an artificial noise beamforming is used to prevent this eavesdropper to decode legitimate users’ message in the downlink. Additionally, the base station has only imperfect channel state information (CSI) of legitimate users which is the practically relevant case. Under the condition of imperfect CSI, a noise leakage on legitimate users’ signal is occurred and it degrades the achievable average secrecy sum rate. In order to reduce this noise leakage, the semi-orthogonal selection having a rotated codebook is proposed to establish a secure communications link. We demonstrate the average secrecy sum rate results of the proposed algorithm for secure multiuser MIMO systems under imperfect CSI through extensive simulation results.

Ergodic Interference Alignment for Spectrum Sharing Radar-Communication Systems

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.

Network control and rate optimization for multiuser MIMO communications

We present a network control and rate optimization solution for multiuser multiple input multiple output (MU-MIMO) communications in wireless networks. This solution is decentralized and includes scheduling and routing of the MU-MIMO communication links that adapt to dynamic channel, interference, and traffic conditions. We start with analyzing the ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations by considering the error, and overhead effects due to channel estimation (training) and quantization (feedback). By taking the practical considerations such as channel estimation, quantization error and in-network interference into account, we show the rate gain with an increasing number of antennas compared with single-input single-output (SISO) systems. Next, we present a distributed channel access protocol to select and activate MU-MIMO configurations with the maximum achievable sum rates using local information on channel, interference, and traffic conditions. Then, we extend this scheduling algorithm to routing via a cross-layer solution based on a decentralized version of the backpressure algorithm. After accounting for the control message overhead, we show that the proposed MU-MIMO scheduling and routing solution improves the stable throughput over the minimum distance routing based on frequency of encounters and single user MIMO communications in a mobile ad hoc network (MANET) setting.

Solving Fractional Polynomial Problems by Polynomial Optimization Theory

This work aims to introduce the framework of polynomial optimization theory to solve fractional polynomial problems (FPPs). Unlike other widely used optimization frameworks, the proposed one applies to a larger class of FPPs, not necessarily defined by concave and convex functions. An iterative algorithm that is provably convergent and enjoys asymptotic optimality properties is proposed. Numerical results are used to validate its accuracy in the non-asymptotic regime when applied to the energy efficiency maximization in multiuser multiple-input multiple-output communication systems.

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

Remarkable research activities and major advances have been occurred over the past decade in multiuser multiple-input multiple-output (MU-MIMO) systems. Several transmission technologies and precoding techniques have been developed in order to exploit the spatial dimension so that simultaneous transmission of independent data streams reuse the same radio resources. The achievable performance of such techniques heavily depends on the channel characteristics of the selected users, the amount of channel knowledge, and how efficiently interference is mitigated. In systems where the total number of receivers is larger than the number of total transmit antennas, user selection becomes a key approach to benefit from multiuser diversity and achieve full multiplexing gain. The overall performance of MU-MIMO systems is a complex joint multi-objective optimization problem since many variables and parameters have to be optimized, including the number of users, the number of antennas, spatial signaling, rate and power allocation, and transmission technique. The objective of this literature survey is to provide a comprehensive overview of the various methodologies used to approach the aforementioned joint optimization task in the downlink of MU-MIMO communication systems.

Energy‐efficient pilot and data power allocation in massive multi‐user multiple‐input multiple‐output communication systems

This study aims to improve the energy efficiency of time-division duplexing massive multi-user multiple-input multiple-output communication systems for both uplink and downlink transmissions. By using minimum mean square error channel estimation, two novel pilot–data power allocation schemes are proposed to minimise the total uplink and downlink transmit power under per-user signal-to-interference-plus-noise ratio (SINR) requirement and per-user power consumption constraints. The proposed schemes take into account the maximum-ratio combining and zero-forcing (ZF) detectors in the uplink transmission together with maximum-ratio transmission and ZF precoder in the downlink transmission. In order to simplify the proposed optimisation problems, lower bounds of the average SINR are derived and used in the power allocation algorithms. The key contribution of this study lies in formulating the original energy-efficient power allocation problem and converting such a complicated optimisation problem to a geometric programming problem. Computer simulation validates the tightness of the derived SINR lower bounds and shows that the proposed schemes can save up to 78% of the total power as compared with the equal power allocation among all the mobile users.

Max–min fair wireless energy transfer for multiple‐input multiple‐output wiretap channels

In this study, the authors study the max–min fairness for wireless energy transfer in a multiuser multiple-input multiple-output communication system with simultaneous wireless information and power transfer. In particular, they aim to maximise the minimum harvested energy among the multiple multi-antenna energy receivers while guaranteeing secure communication for multi-antenna information receiver. The dual use of artificial noise to facilitate both wireless energy transfer and secure communication is exploited in the authors’ proposed problem. Both scenarios of perfect and imperfect channel state information (CSI) known at the transmitter are considered. For the perfect CSI case, the formulated max–min energy harvesting (MM-EH) problem is non-convex and intractable. To circumvent it, an iterative optimisation algorithm based on Taylor series expansion is proposed. Then, they turn their attention to the imperfect CSI case, where a max–min robust energy harvesting (MMR-EH) problem is considered. Though the MMR-EH problem is more complicated than the MM-EH problem, they reveal that the iterative optimisation method can be extended to the solution of the former, wherein the S-procedure is introduced. Simulation results show the efficiency of their proposed solutions in terms of energy harvesting.

A Framework to Construct 3-Dimensional Complementary Codes for Multi-User MIMO Systems

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.

Sum-Rate Maximization in Distributed-Antenna Heterogeneous MIMO Downlinks: Application to Measured Channels

In a distributed antenna multiple-input multiple- output (MIMO) multiuser channel, multiple nodes simultaneously access the wireless channel by cooperating to achieve virtual MIMO links, enabling improved exploitation of the channel spatial dimensions. However, practical considerations dictate that in such a system, the transmit power from each cooperating node must be constrained in a per-antenna power constraint, which differs from the sum-power constraint typical of multiuser MIMO signaling. Furthermore, existing multiuser MIMO communication algorithms are appropriate for specific assumptions regarding the signaling strategy allowed. This paper provides a general framework able to accommodate a variety of multiuser MIMO channel topologies, precoding techniques (linear or nonlinear), and power constraints including the per-antenna constraint appropriate for the cooperative MIMO channel involving heterogeneous nodes. In contrast to prior work incorporating per-antenna power constraints, the algorithm enables reduced implementation and computational complexity by avoiding the requirement of numerical optimization. Simulation results using both modeled and measured cooperative channel responses demonstrate that the sum rate of a cooperative broadcast channel with a per-antenna power constraint is very close to the optimal bound achieved using a sum-power constraint, even in practical scenarios. Additional results demonstrate the straightforward application of the algorithm to different practical multiuser topologies.

Improved Linear Transmit Processing for Single-User and Multi-User MIMO Communications Systems

In this paper, we propose a novel linear transmit precoding strategy for multiple-input, multiple-output (MIMO) systems employing improper signal constellations. In particular, improved zero-forcing (ZF) and minimum mean square error (MMSE) precoders are derived based on modified cost functions, and are shown to achieve a superior performance without loss of spectrum efficiency compared to the conventional linear and nonlinear precoders. The superiority of the proposed precoders over the conventional solutions are verified by both simulation and analytical results. The novel approach to precoding design is also applied to the case of an imperfect channel estimate with a known error covariance as well as to the multi-user scenario where precoding based on the nullspace of channel transmission matrix is employed to decouple multi-user channels. In both cases, the improved precoding schemes yield significant performance gain compared to the conventional counterparts.