Distributed and Joint Optimization of Precoding and Power for User-Centric Cell-Free Massive MIMO

TL;DR

This paper introduces a distributed precoding and power control scheme for cell-free massive MIMO that reduces signaling overhead while maintaining centralized performance levels.

Contribution

It proposes a novel distributed optimization method combining null space precoding and dual decomposition for efficient interference management.

Findings

Achieves centralized performance with fewer iterations

Reduces signaling overhead between CPU and APs

Provides closed-form solutions for distributed optimization

Abstract

In the cell-free massive multiple-input multiple-output (CF mMIMO) system, the centralized transmission scheme is widely adopted to manage the inter-user interference. Unfortunately, its implementation is limited by the extensive signaling overhead between the central process unit (CPU) and the access points (APs). To solve this problem, we propose a distributed downlink transmission scheme in this letter. First, the null space-based precoding is used to cancel the interference to partial users, where only a portion of channel state information (CSI) needs to be shared among the AP cluster. Based on this, the dual decomposition method is adopted to jointly optimize the precoder and power control, where the calculation can be performed independently by each AP cluster with closed-form expression. With very few iterations, our distributed scheme achieves the same performance as the centralized one. Moreover, it significantly reduces the information exchange to the CPU.