Cell-Free MIMO Research Articles

Throughput Maximization-Based AP Clustering Methods in Downlink Cell-Free MIMO Under Partial CSI Condition

Throughput Maximization-Based AP Clustering Methods in Downlink Cell-Free MIMO Under Partial CSI Condition

Uplink Resource Allocation Optimization for User-Centric Cell-Free MIMO Networks

Uplink Resource Allocation Optimization for User-Centric Cell-Free MIMO Networks

Distributed Joint Beamforming for RIS-assisted Cell-Free MIMO with Discrete Phase Shifts

Abstract Both reconfiurable intelligent surface (RIS) and cell-free multiple-input multiple-output (CF-MIMO) system are holding promise to become the predominant research direction in 6G networks. This paper studies the problem of weighted sum-rate maximization(WSR) in RIS-assisted CF-MIMO networks with discrete phase shifts. We utilize alternating optimization (AO) to iteratively calculate active and passive beamforming. At access points (APs) side, we employ a distributed algorithm to design the active beamforming, leveraging information interact among APs without centralized designing at central processing unit(CPU). Facing the constraint of discrete phase shift in RIS, we adopt semidefinite relaxation(SDR) projection and proximal gradient descent(PGD) to design the passive beamforming respectively. Simulation results indicate that our proposed algorithms achieve performance comparable to the distributed framework with continuous phase shift while reducing the computational time.

On Lattice Network Coding Based Cell-Free MIMO With Uncoordinated Base Stations

On Lattice Network Coding Based Cell-Free MIMO With Uncoordinated Base Stations

Handoffs in User-Centric Cell-Free MIMO Networks: A POMDP Framework

Handoffs in User-Centric Cell-Free MIMO Networks: A POMDP Framework

Multi-Antenna Array-Based Massive MIMO for B5G/6G: State of the Art, Challenges, and Future Research Directions

This comprehensive article explores the massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, cell-free MIMO, and security considerations, this article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights the challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of federated learning in M-MIMO systems. By examining these cutting-edge developments, this article aims to advance knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

Clustering and Scheduling With Fairness Based on Information Rates for Cell-Free MIMO Networks

Clustering and Scheduling With Fairness Based on Information Rates for Cell-Free MIMO Networks

Federated Cell-Free MIMO in Nonterrestrial Networks: Architectures and Performance

Federated Cell-Free MIMO in Nonterrestrial Networks: Architectures and Performance

Dynamic Scheduling and Power Allocation with Random Arrival Rates in Dense User-Centric Scalable Cell-Free MIMO Networks

In this paper, we address scheduling methods for queue stabilization and appropriate power allocation techniques in downlink dense user-centric scalable cell-free multiple-input multiple-output (CF-MIMO) networks. Scheduling is performed by the central processing unit (CPU) scheduler using Lyapunov optimization for queue stabilization. In this process, the drift-plus-penalty is utilized, and the control parameter V serves as the weighting factor for the penalty term. The control parameter V is fixed to achieve queue stabilization. We introduce the dynamic V method, which adaptively selects the control parameter V considering the current queue backlog, arrival rate, and effective rate. The dynamic V method allows flexible scheduling based on traffic conditions, demonstrating its advantages over fixed V scheduling methods. In cases where UEs scheduled with dynamic V exceed the number of antennas at the access point (AP), the semi-orthogonal user selection (SUS) algorithm is employed to reschedule UEs with favorable channel conditions and orthogonality. Dynamic V shows the best queue stabilization performance across all traffic conditions. It shows a 10% degraded throughput performance compared to V = 10,000. Max-min fairness (MMF), sum SE maximization, and fractional power allocation (FPA) are widely considered power allocation methods. However, the power allocation method proposed in this paper, combining FPA and queue-based FPA, achieves up to 60% better queue stabilization performance compared to MMF. It is suitable for systems requiring low latency.

Iterative Detection and Decoding With Log-Likelihood Ratio Based Access Point Selection for Cell-Free MIMO Systems

Iterative Detection and Decoding With Log-Likelihood Ratio Based Access Point Selection for Cell-Free MIMO Systems

A Distributed Machine Learning-Based Approach for IRS-Enhanced Cell-Free MIMO Networks

A Distributed Machine Learning-Based Approach for IRS-Enhanced Cell-Free MIMO Networks

Cost-Aware Resource Allocation for Hybrid Multiple Access in Cell-Free MIMO System

Cost-Aware Resource Allocation for Hybrid Multiple Access in Cell-Free MIMO System

Fully Distributed Cell-Free MIMO Systems: Architecture, Algorithm, and Testbed Experiments

Fully Distributed Cell-Free MIMO Systems: Architecture, Algorithm, and Testbed Experiments

Capacity Optimization for Cell-Free MIMO Systems With Mean and Covariance Feedback

Capacity Optimization for Cell-Free MIMO Systems With Mean and Covariance Feedback

Deep Reinforcement Learning Assisted Multi-Operator Spectrum Sharing in Cell-Free MIMO Networks

Deep Reinforcement Learning Assisted Multi-Operator Spectrum Sharing in Cell-Free MIMO Networks

Joint Long-Term Energy Efficient Scheduling and Beamforming Design for URLLC in Cell-Free MIMO Systems

Joint Long-Term Energy Efficient Scheduling and Beamforming Design for URLLC in Cell-Free MIMO Systems

RIS-Aided Cell-Free MIMO System: Perfect and Imperfect CSI Design for Energy Efficiency

Thanks to the development of the 6th generation mobile network that makes it possible for us to move towards an intelligent ubiquitous information society, among which some novel technologies represented by cell-free network has also attracted widespread academic attention. Cell-free network has brought distinguished gains to the network capacity with its strong ability against inter-cell interference. Unfortunately, further improvement demands more base stations (BSs) to be settled, which incurs steep cost increase. To address this issue, reconfigurable intelligent surface (RIS) with low cost and power consumption is introduced in this paper to replace some of the trivial BSs in the system, then, a RIS-aided cell-free network paradigm is formulated. Our objective is to solve the weighted sumrate (WSR) maximization problem by jointly optimizing the beamforming design at BSs and the phase shift of RISs. Due to the non-convexity of the formulated problem, this paper investigates a joint optimizing scheme based on block coordinate descent (BCD) method. Subsequently, on account of the majority of the precious work reposed perfect channel state information (CSI) setup for the ultimate performance, this paper also extends the proposed algorithm to the case wherein CSI is imperfect by utilizing successive convex approximation (SCA). Finally, simulation results demonstrate that the proposed scheme shows great performance and robustness in perfect CSI scenario as well as the imperfect ones.

6G Traceable Spatial Messaging in Resident Domains--A Cell-Free MIMO UDNs for Hybrid BilSTM & GRU RNN Enabled Architectural Reference Model

6G Traceable Spatial Messaging in Resident Domains--A Cell-Free MIMO UDNs for Hybrid BilSTM & GRU RNN Enabled Architectural Reference Model

6G Traceable Spatial Messaging in Resident Domains—A Cell-Free MIMO UDNs for Hybrid BilSTM & GRU RNN Enabled Architectural Reference Model (ARM)

6G Traceable Spatial Messaging in Resident Domains—A Cell-Free MIMO UDNs for Hybrid BilSTM & GRU RNN Enabled Architectural Reference Model (ARM)

A Hybrid BilSTM & GRU RNN Enabled Architectural Reference Model (ARM) in 6G Cell-Free MIMO UDNs for Traceable Spatial Messaging in Resident Domains

A Hybrid BilSTM & GRU RNN Enabled Architectural Reference Model (ARM) in 6G Cell-Free MIMO UDNs for Traceable Spatial Messaging in Resident Domains