Cell-Free Massive MIMO with Large-Scale Fading Decoding and Dynamic Cooperation Clustering

TL;DR

This paper explores user-centric cell-free massive MIMO uplink systems, proposing a large-scale fading decoding framework with dynamic cooperation clustering, optimized fronthaul load, and efficient power control to enhance spectral efficiency.

Contribution

It introduces a nearly optimal second-layer decoding scheme and an efficient fixed-point algorithm for joint LSFD weights and power control in cell-free massive MIMO.

Findings

Reduced fronthaul signaling load with the proposed decoding scheme

Optimal max-min fair power control achieved via fixed-point algorithm

Simulations provide new insights into practical implementation

Abstract

This paper considers the uplink of user-centric cell-free massive MIMO (multiple-input multiple-output) systems. We utilize the user-centric dynamic cooperation clustering (DCC) framework and derive the achievable spectral efficiency with two-layer decoding that is divided between the access points and the central processing unit (CPU). This decoding method is also known as large-scale fading decoding (LSFD). The fronthaul signaling load is analyzed and a nearly optimal second-layer decoding scheme at the CPU is proposed to reduce the fronthaul requirements compared to the optimal scheme. We also revisit the joint optimization of LSFD weights and uplink power control and show that the corresponding max-min fair optimization problem can be solved optimally via an efficient fixed-point algorithm. We provide simulations that bring new insights into the cell-free massive MIMO implementation.