Decentralized Beamforming Design for Intelligent Reflecting Surface-enhanced Cell-free Networks

TL;DR

This paper introduces a decentralized beamforming framework for IRS-enhanced cell-free networks, improving capacity and reducing costs by enabling local updates with an ADMM algorithm, approaching centralized performance.

Contribution

It proposes a novel decentralized beamforming design using ADMM for IRS-assisted cell-free networks, addressing cost and scalability issues.

Findings

IRS significantly increases system sum-rate.

The proposed method outperforms existing decentralized approaches.

Performance approaches centralized schemes with more iterations.

Abstract

Cell-free networks are considered as a promising distributed network architecture to satisfy the increasing number of users and high rate expectations in beyond-5G systems. However, to further enhance network capacity, an increasing number of high-cost base stations (BSs) are required. To address this problem and inspired by the cost-effective intelligent reflecting surface (IRS) technique, we propose a fully decentralized design framework for cooperative beamforming in IRS-aided cell-free networks. We first transform the centralized weighted sum-rate maximization problem into a tractable consensus optimization problem, and then an incremental alternating direction method of multipliers (ADMM) algorithm is proposed to locally update the beamformer. The complexity and convergence of the proposed method are analyzed, and these results show that the performance of the new scheme can asymptotically approach that of the centralized one as the number of iterations increases. Results also show that IRSs can significantly increase the system sum-rate of cell-free networks and the proposed method outperforms existing decentralized methods.