Multiuser MIMO Systems Research Articles

Modeling and Performance Analysis of Vertical Heterogeneous Networks Under 3D Blockage Effects and Multiuser MIMO Systems

Modeling and Performance Analysis of Vertical Heterogeneous Networks Under 3D Blockage Effects and Multiuser MIMO Systems

Statistical spatial information based power optimization algorithm for multi-user massive MIMO systems

Power optimization has a significant role in multi-user massive multiple-input and multiple-output (mMIMO) wireless communication systems, whereas the acquisition of instantaneous channel state information (I-CSI) is a serious challenge in practical scenarios. The statistical spatial information (SPI), which contains angle-of-departures (AoDs) and corresponding large-scale fading factors, is slowly varying. The power optimization based on SPI to improve system performance needs to be explored for multi-user mMIMO systems. In this paper, two novel algorithms for SPI-based power optimization are proposed to maximize the ergodic sum-rate (ESR) under total power constraint for the system. Specifically, the minorization-maximization-based power optimization (MM-PO) algorithm and the closed-form power optimization (CF-PO) algorithm are proposed utilizing the minorization-maximization (MM) method and the fractional programming (FP) method, respectively. Moreover, the ESR is expressed based on the extracted SPI. The approximate expression of the ESR is derived. The complexity of the algorithms depends on the number of users, and the algorithms are scalable in the system. The proposed algorithms can effectively achieve the advantages of SPI while being robust to the uncertainty of I-CSI. Simulation results verify the ESR of our two proposed algorithms is 1.47 and 1.4 times higher than that of the equal power allocation algorithm at a high SNR when the number of antenna and user are equal to 64 and 20, respectively.

Implementing intelligent‐based sparse channel estimation in Multi User‐Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing system with hybridized optimization algorithm

SummaryThe channel plays a significant role as the multipath in Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) systems. The precoding‐based channel estimation algorithms estimate the channel capacity at the receiver node and they provide efficient channel estimates under worst case channel scenarios. To estimate the channel capacity in the mobile node, semi‐blind scenario is a crucial task in Multi User (MU) MIMO systems. Therefore, a semi blind sparse channel estimation algorithm is demonstrated in the MU‐MIMO system to provide better performance. In the transmitter side, the signal modulation is performed with the help of Quadrature Phase Shift Keying (QPSK), and the modulated signal is given to Pulse Shaping Algorithm (PSA) to reduce the inter‐carrier interference as well as inter symbol interference. At each transmitter, the Inverse Fast Fourier Transforms (IFFT) technique is used for mapping the symbols and then the mapped signal is send to the receiver. In the receiver side, the FFT, pulse reshaping, and QPSK demodulation blocks are serially connected and perform inverse operations of the transmitter in the receiver. Then, the sparse channel is estimated at the receiver by using the semi blind sparse algorithm, where the parameters are optimized by using the Hybridized Drosophila with Virus Colony Search Optimization (HD‐VCSO). The objective function of the developed sparse channel estimation is the reduction of Minimum Mean Square Error (MMSE) in the channel. The performance of the developed sparse channel estimation algorithm is analyzed through different conventional algorithms to validate the effectiveness of the proposed algorithm.

Joint Optimization of IRS-Assisted Multiuser MIMO Systems With Low-Resolution DACs

Joint Optimization of IRS-Assisted Multiuser MIMO Systems With Low-Resolution DACs

Blind Signal Reception in Downlink Generalized Spatial Modulation Multiuser MIMO System Based on Minimum Output Energy

Blind Signal Reception in Downlink Generalized Spatial Modulation Multiuser MIMO System Based on Minimum Output Energy

Performance analysis of multiple RISs aided multi-user mmWave MIMO systems

Performance analysis of multiple RISs aided multi-user mmWave MIMO systems

Spectral efficiency of hybrid precoding and combining design for mm-Wave multi-user massive MIMO systems

Spectral efficiency of hybrid precoding and combining design for mm-Wave multi-user massive MIMO systems

Hybrid Precoding Design in Multi-User mmWave Massive MIMO Systems for BER Minimization

Hybrid Precoding Design in Multi-User mmWave Massive MIMO Systems for BER Minimization

Location-driven beamforming for massive multi-user MIMO systems

Location-driven beamforming for massive multi-user MIMO systems

Improving Signal Detector by Precoding in Uplink Multiuser MIMO System

Improving Signal Detector by Precoding in Uplink Multiuser MIMO System

Channel Estimation for BIOS-Assisted Multi-User MIMO Systems: A Heterogeneous Two-timescale Strategy

Channel Estimation for BIOS-Assisted Multi-User MIMO Systems: A Heterogeneous Two-timescale Strategy

Numerical Evaluation of the MU-MIMO Beamforming Performance with Channel Estimation

This paper presents the numerical evaluation of the ZF beamforming algorithm and DFT precoding using the LS channel estimation in the multiuser multiantenna (MU-MIMO) downlink system. The sum rate performance depending on a number of users are presented. The arising inter user correlation degrades the sum rate (spectral efficiency) performance of multiuser MIMO system especially in scenarios where the number of users is larger than the number of antennas at the BS. For MIMO channel simulation the QuaDRiGa channel model reflecting the real propagation conditions is used. The obtained performance of MU-MIMO ZF precoding in spatially correlated channel are compared with DFT precoding based on the empirical cumulative density function of the sum rate of multiple users. Numerical results show that the ZF precoder outperforms the DFT precoder in channel with less spatial correlation. The DFT precoder in spatially more correlated channel has advantage over ZF precoder.

Rate-Splitting Multiple Access for Quantized Multiuser MIMO Communications

This paper investigates the sum spectral efficiency maximization problem in downlink multiuser multiple-input multiple-output systems with low-resolution quantizers at an access point (AP) and users. We consider rate-splitting multiple access (RSMA) to enhance spectral efficiency by offering opportunities to boost achievable degree-of-freedom. Optimizing RSMA precoders, however, is highly challenging due to the minimum rate constraint when determining the common rate. The quantization errors coupled with the precoders make the problem more complicated. In this paper, we develop a novel RSMA precoding algorithm incorporating quantization errors for maximizing the sum spectral efficiency. To this end, we first obtain an approximate spectral efficiency in a smooth function. Subsequently, we derive the first-order optimality condition in the form of the nonlinear eigenvalue problem (NEP). We propose a computationally efficient algorithm to find the principal eigenvector of the NEP as a sub-optimal solution. We also extend the weighted minimum mean square error-based RSMA precoding to the considered quantization system. Simulation results validate the proposed methods. The key benefit of using RSMA over spatial division multiple access (SDMA) comes from the ability of the common stream to balance between the channel gain and quantization error in multiuser MIMO systems with different quantization resolutions.

Energy efficiency optimization algorithm based on RIS and D2D for multi-user MIMO system

Reconfigurable Intelligent Surface (RIS) is composed of reconfigurable passive components, which can realize on-demand customization of wireless communication environment. Device-to-Device (D2D) communication is one of the essential technologies to improve the capacity and spectrum efficiency of network system. In this paper, we propose an energy efficiency optimization algorithm based on RIS and D2D assisted multi-user MIMO system. The purpose is to maximize the energy efficiency of the system by jointly optimizing subcarrier allocation, power allocation and passive beamforming at RIS. We first formulate the energy efficiency maximization problem with the constraints of different user rate, power, subcarrier allocation and phase. Since it is a non-convex problem, we use an alternating optimization (AO) algorithm to decouple it into three sub-problems. The solutions of these three sub-problems are solved by subcarrier allocation based on channel strength, SCA algorithm, Dinkelbach algorithm and Riemannian gradient algorithm respectively. Simulation results show that the proposed scheme can significantly improve the energy efficiency.

Beyond Integer-Forcing Receiver for Lattice-Code Based Multi-User MIMO System

Beyond Integer-Forcing Receiver for Lattice-Code Based Multi-User MIMO System

Joint online 3D trajectory optimisation and power allocation of UAVs as mobile access points in a downlink distributed multi-user MIMO system

Unmanned aerial vehicles (UAVs) are introduced as one of the key-enablers for 5G beyond networks due to their low cost and flexible deployment, and mobility degrees-of-freedom. Moreover, low sensitivity to blockage and uncorrelated channels in distributed multiple-input multiple-output (D-MIMO) systems, and their extension which is called cell-free massive MIMO, have made them an attractive research field. The location and number of access points (APs) in D-MIMO systems highly influence the system performance in terms of energy and spectral efficiency that can be handled by UAVs mobility and flexible deployment. In this paper, joint power allocation, and 3D trajectory design in a D-MIMO system for a downlink scenario where multiple UAVs serve as mobile APs (MbAPs) is investigated. Contrary to the existing works in multi-mobile base stations, we introduce space-division multiple access (SDMA) for the online trajectory design as a multi-access technology which does not suffer from the non-casual channel property in traditional trajectory designs. In the proposed design, the smallest user’s ergodic rate lower bound is maximised by jointly optimising MbAPs’ 3D trajectory and transmit power. The block coordinate descent (BCD) algorithm is deployed to break the main problem into two sub-problems and iteratively optimise over the two. Considering the non-convex nature of both of sub-problems, successive convex approximation is also exploited. For performance analysis, complexity and convergence property of the proposed algorithm are investigated. Finally, numerical results validate the improved performance of the proposed system in a practical scenario, where users can connect and disconnect to and from the network.

Low complexity nonlinear detection for multiuser hybrid MIMO systems and performance analysis

This paper proposes an analytical framework and a system of distortion-aware receiver structures for single-carrier uplink hybrid beamforming-based multiple-input-multiple-output (MIMO) channels. Proposed single-user processing units cooperate at the base station (BS) in an iterative manner for multi-user symbol detection under hardware impairments. Firstly, in the proposed system, an iterative nonlinear interference cancellation (nIC) based on feedforward neural network (NN) modeling is developed to eliminate the nonlinear distortion effects of power amplifiers (PAs). Furthermore, depending on the fading pattern of the instantaneous channel, it is analytically shown that a large gain may be applied to the distortion signal during the equalization stage, which yields distortion amplification causing a significant decrease in the signal-to-distortion-plus-noise ratio (SDNR). A reduced complexity distortion aware detector, based on a bank of fractionally delayed iterative block decision feedback equalization (IB-DFE) receivers, is introduced to adjust the combiner weights for fractionally delayed IB-DFE outputs so that distortion power is minimized before detection. Consequently, multi-user detection capability is enhanced considerably. Secondly, an asymptotic SDNR analysis is performed. The theoretical analysis, verified via numerical evaluations, clearly shows that distortion amplification limits the achievable SDNR at the BS, and the proposed reduced complexity multi-user receiver architecture improves the BER performance by effectively mitigating this effect.

Bit-Metric Decoding Rate in Multi-User MIMO Systems: Applications

This is the second part of a two-part paper that focuses on link-adaptation (LA) and physical layer (PHY) abstraction for multi-user MIMO (MU-MIMO) systems with non-linear receivers. The first part proposes a new metric, called bit-metric decoding rate (BMDR) for a detector, as being the equivalent of post-equalization signal-to-interference-noise ratio (SINR) for non-linear receivers. Since this BMDR does not have a closed form expression, a machine-learning based approach to estimate it effectively is presented. In this part, the concepts developed in the first part are utilized to develop novel algorithms for LA, dynamic detector selection from a list of available detectors, and PHY abstraction in MU-MIMO systems with arbitrary receivers. Extensive simulation results that substantiate the efficacy of the proposed algorithms are presented.

Numerical Evaluation of the MU-MIMO Beamforming Performance with User Selection Algorithm

This paper presents the numerical evaluation of the ZF beamforming algorithm using the user selection in the multiuser multiantenna (MU-MIMO) downlink system. Two user selection algorithm – semiorthogonal user selection and greedy user selection are numerically evaluated based on the open source MIMO channel model. The sum rate performance depending on number of users are presented. The arising inter user correlation degrades the sum rate (spectral efficiency) performance of multiuser MIMO system especially in scenarios where the number of users is larger than the number of antennas at the BS. The selection of users is based on the orthogonality of the channels among selected users. For MIMO channel simulation the QUADRIGA channel model reflecting the real propagation conditions is used. The obtained performance of MU-MIMO ZF precoding in spatially correlated channel are compared based on the empirical cumulative density function of the sum rate of multiple users. Numerical results show that the ZF precoder using user selection (G ZF) outperforms the ZF precoder with random user selection in spectral efficiency. The greedy user selection in spatially correlated channel has advantage to semi-orthogonal user selection. It isobserved that as the increasing the number of served users used for selection the greedy user selection gives better performance than semi-orthogonal algorithm.

Performance Evaluation of Hybrid Precoder Design for Multi-User Massive MIMO Systems with Low-Resolution ADCs/DACs

This paper presents a comprehensive analysis and design of a hybrid precoding system tailored for mmWave multi-user massive MIMO systems in both downlink and uplink scenarios. The proposed system employs a two-stage precoding approach, incorporating UQ and NUQ techniques, along with low-resolution DACs in downlink and ADCs in uplink to address hardware limitations. The system considers Zero Forcing and Minimum Mean Square Error algorithms as digital precoding methods for the uplink scenario, while exploring the impact of different DAC resolutions on system performance. Extensive simulations reveal that the proposed system surpasses conventional analog beamforming methods, particularly in multi-user scenarios involving inter-user interference. In downlink, the system demonstrates a trade-off between SE and EE, achieving higher Energy Efficiency with NUQ. In uplink, NUQ and UQ converters exhibit similar performance trends regardless of the chosen combiner algorithm. The proposed system attains enhanced Spectral and Energy Efficiency while maintaining reduced complexity and overhead. The study significantly contributes to the advancement of efficient and effective mmWave multi-user massive MIMO systems by providing a thorough analysis of various quantization schemes and precoding techniques. The findings of this research are expected to aid in the optimization of 5G and beyond technologies, particularly in high-density deployment scenarios.