Cell-Free Massive MIMO Systems Research Articles

Pilot Assignment for Cell Free Massive MIMO Systems: A Successive Interference Cancellation Approach

In the contemporary era, considerable attention has been directed towards exploring cell-free massive multiple-input multiple-output (CF-M-MIMO) systems. This novel network paradigm has gained prominence as a potential solution for tackling the persistent challenge of inter-cell interference prevalent in traditional cellular MIMO networks. This study investigates a pilot assignment approach based on Successive Interference Cancellation (SIC) aimed at alleviating pilot contamination issues inherent in CF-M-MIMO systems. Through comprehensive numerical analyses and simulations, we demonstrate the efficacy and enhanced performance of the SIC-based approach competed with common random and greedy pilot assignment strategies. The proposed methodology addresses the critical challenge of pilot contamination, a phenomenon that severely impacts system performance and spectral efficiency. By iteratively decoding signals and canceling interference, the SIC algorithm optimizes pilot assignments, resulting in improved data rates and more efficient resource utilization. Our findings underscore the robustness and scalability of the SIC-based scheme across diverse system parameters and deployment scenarios, affirming its potential as a promising solution for enhancing the performance of CF-M-MIMO systems. Overall, this study contributes valuable insights into the design and optimization of pilot assignment strategies, offering a pathway for further research and development in the field of CF-M-MIMO systems.

On the total energy consumption of scalable cache-aided multi-CPU cell-free massive MIMO systems

In conventional cell-free (CF) systems, the scalability and feasibility are hindered by the fact that a single central processing unit (CPU) manages all access points and the stringent synchronization requirement for coherent transmission (CT) across the entire network. Multi-CPU CF systems emerge as a scalable and feasible alternative, yet they still encounter the typical CF system challenge of high downlink transmit energy consumption from extensive fronthaul and backhaul transmissions. To tackle this issue, we propose a scalable downlink partial coherent transmission (PCT) strategy for multi-CPU CF systems to provide high spectral efficiency (SE), reduce transmission time and thereby lower energy consumption, while keeping decoding complexity manageable. Based on the PCT strategy, we introduce scalable cache-aided multi-CPU CF systems and develop the corresponding total energy consumption (TEC) model. A successive convex approximation algorithm is proposed to obtain the suboptimal cache placement to minimize the TEC. Simulation results indicate that the proposed PCT-based scalable cache-aided multi-CPU CF systems can significantly reduce the TEC and consistently maintain the TEC at a relatively low level across all Zipf parameters by leveraging the high SE of CT and the independent transmission of non-coherent transmission.

Joint AP Selection and Grey Wolf Optimization Based Pilot Design for Cell-Free Massive MIMO Systems

Joint AP Selection and Grey Wolf Optimization Based Pilot Design for Cell-Free Massive MIMO Systems

Downlink Transmissions of UAV-RIS-Assisted Cell-Free Massive MIMO Systems: Location and Trajectory Optimization.

In this paper, we investigate a cell-free massive multiple-input multiple-output (CF-mMIMO) system with a reconfigurable intelligent surface (RIS) carried by an unmanned aerial vehicle (UAV), called the UAV-RIS. Compared with the RIS located on the ground, the UAV-RIS has a wider coverage that can reflect all signals from access points (APs) and user equipment (UE). By correlating the UAV location with the Rician K-factor, we derive a closed-form approximation of the UE achievable downlink rate. Based on this, we obtain the optimal UAV location and RIS phase shift that can maximize the UE sum rate through an alternating optimization method. Simulation results have verified the accuracy of the derived approximation and shown that the UE sum rate can be significantly improved with the obtained optimal UAV location and RIS phase shift. Moreover, we find that with a uniform UE distribution, the UAV-RIS should fly to the center of the system, while with an uneven UE distribution, the UAV-RIS should fly above the area where UEs are gathered. In addition, we also design the best trajectory for the UAV-RIS to fly from its initial location to the optimal destination while maintaining the maximum UE sum rate per time slot during the flight.

Active and passive beamforming in RIS-assisted cell-free massive MIMO systems: an edge computing perspective

Active and passive beamforming in RIS-assisted cell-free massive MIMO systems: an edge computing perspective

Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems

Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems

Two-Timescale Transmission Design for RIS-Aided Cell-Free Massive MIMO Systems

Two-Timescale Transmission Design for RIS-Aided Cell-Free Massive MIMO Systems

Fingerprint-Based 3D Hierarchical Localization for Cell-Free Massive MIMO Systems

Fingerprint-Based 3D Hierarchical Localization for Cell-Free Massive MIMO Systems

Scalable Cache-Aided Cell-Free Massive MIMO Systems

Scalable Cache-Aided Cell-Free Massive MIMO Systems

An Analytical Reliability Performance Assessment of Cell-Free Massive MIMO Systems for 5G and Beyond Cellular Networks

In today‟s realm, the 5G cellular networks offer a new era of fully digital environment by connecting people anywhere anytime. This era requires inspiring demands to the networks in terms of spectral and energy efficiencies, low-latency and ultra-reliable communications. A major development to deal with these unparalleled demands is the introduction of Cell- Free Massive MIMO (CF mMIMO) systems to the cellular network. In recent years, mathematical foundations have been laid for a CF mMIMO communication system to evaluate the spectral and energy efficiencies given the number of access points. Various existing literatures have adopted mathematical models to formulate closed-form expressions for these efficiencies using uncorrelated Rayleigh fading for simple linear processing detectors. In this paper, we try to address a compelling and interesting question which has not received much attention lately. The question is how to evaluate the reliability of a connected user terminal in both a CF mMIMO and conventional mMIMO system? We answer this question by first analyzing the signal models for both systems assuming exact channel estimates and consider an uncorrelated Rayleigh fading channel model. The exact Bit Error Rate, as a reliability assessment, in closed-form are then derived based on strong mathematical foundations, which are simple to numerically evaluate in Matlab R2022, for MPSK and MQAM modulation schemes. The mathematical models presented in this work can be used in 5G and Beyond 5G networks to evaluate the distributions of error rates for a user given the number of Access points or Base Station antennas and modulation scheme. Machine Learning algorithms can be applied to the analytical expressions with a view to predict the error performance of a user terminal given the fading characteristic of the propagation environmen

Coverage Probability and Ergodic Capacity of Cell-Free Massive MIMO System

Coverage Probability and Ergodic Capacity of Cell-Free Massive MIMO System

Novel Beamforming Design for IRS-Assisted Cell-Free Massive MIMO Systems

Novel Beamforming Design for IRS-Assisted Cell-Free Massive MIMO Systems

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications

Distributed Hybrid Precoding for Edge-Computing-Assisted Cell-Free Massive MIMO Systems With Local CSI

Distributed Hybrid Precoding for Edge-Computing-Assisted Cell-Free Massive MIMO Systems With Local CSI

Fractional Programming-Based Uplink Transmission Power Allocation for User-Centric Cell-Free Massive MIMO Systems

Fractional Programming-Based Uplink Transmission Power Allocation for User-Centric Cell-Free Massive MIMO Systems

Outage Probability Analysis and Bit Allocation for Uplink Cell-Free Massive MIMO Systems With Low-Precision ADCs

Outage Probability Analysis and Bit Allocation for Uplink Cell-Free Massive MIMO Systems With Low-Precision ADCs

STAR-RIS Assisted Cell-Free Massive MIMO System Under Spatially-Correlated Channels

STAR-RIS Assisted Cell-Free Massive MIMO System Under Spatially-Correlated Channels

Heterogeneous Graph Neural Network for Power Allocation in Multicarrier-Division Duplex Cell-Free Massive MIMO Systems

In order to maximize the spectral efficiency (SE) in multicarrier-division duplex (MDD) enabled cell-free massive MIMO (CF-mMIMO), a heterogeneous graph neural network (HGNN), referred to as CF-HGNN, is specifically introduced to optimize the power allocation (PA). To efficiently manage the interference invoked, a meta-path based mechanism is applied in CF-HGNN to enable individual access point (AP) and mobile station (MS) nodes to aggregate information from the interfering and communication paths with different priorities during message passing. Moreover, the proposed CF-HGNN employs the adaptive node embedding layer and adaptive output layer to make it scalable to the various numbers of APs, MSs and subcarriers. For comparison, a quadratic transform and successive convex approximation (QT-SCA) algorithm is proposed to solve the PA problem in classic way. Numerical results show that CF-HGNN is capable of achieving 99% of the SE achievable by QT-SCA but using only 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> times of its operation time, and it can outperform the conventional learning-based and greedy unfair methods in terms of SE performance. Furthermore, CF-HGNN exhibits good scalability to the CF networks with various numbers of nodes and subcarriers, and also to the large-scale CF networks when assisted by user-centric clustering.

Performance Analysis for User-Centric Cell-Free Massive MIMO Systems With Hardware Impairments and Multi-Antenna Users

Performance Analysis for User-Centric Cell-Free Massive MIMO Systems With Hardware Impairments and Multi-Antenna Users

Joint Access Points-User Association and Caching Placement Strategy for Cell-Free Massive MIMO Systems Based on Soft Actor-Critic Algorithm

Joint Access Points-User Association and Caching Placement Strategy for Cell-Free Massive MIMO Systems Based on Soft Actor-Critic Algorithm