Distributed Activity Detection for Cell-Free Hybrid Near-Far Field Communications

TL;DR

This paper introduces a distributed hybrid near-far field activity detection method for cell-free massive MIMO, addressing the challenge of expanding near-field regions with increasing antennas, and demonstrates its superior performance through theoretical analysis and simulations.

Contribution

It proposes a novel covariance-based distributed detection algorithm for hybrid near-far field scenarios in cell-free massive MIMO systems, incorporating a new coordinate descent method.

Findings

The proposed method outperforms existing approaches in detection accuracy.

Theoretical analysis confirms the impact of hybrid near-far channels on performance.

Simulation results validate the effectiveness of the distributed algorithm.

Abstract

A great amount of endeavor has recently been devoted to activity detection for massive machine-type communications in cell-free massive MIMO. However, in practice, as the number of antennas at the access points (APs) increases, the Rayleigh distance that separates the near-field and far-field regions also expands, rendering the conventional assumption of far-field propagation alone impractical. To address this challenge, this paper considers a hybrid near-far field activity detection in cell-free massive MIMO, and establishes a covariance-based formulation, which facilitates the development of a distributed algorithm to alleviate the computational burden at the central processing unit (CPU). Specifically, each AP performs local activity detection for the devices and then transmits the detection result to the CPU for further processing. In particular, a novel coordinate descent algorithm based on the Sherman-Morrison-Woodbury update with Taylor expansion is proposed to handle the local detection problem at each AP. Moreover, we theoretically analyze how the hybrid near-far field channels affect the detection performance. Simulation results validate the theoretical analysis and demonstrate the superior performance of the proposed approach compared with existing approaches.