Optimal Joint Radar and Communication User Association in Cell-Free mMIMO Systems

TL;DR

This paper introduces a joint radar and communication user association framework for cell-free mMIMO systems, optimizing access point selection to enhance both data rates and sensing accuracy, a novel approach in the field.

Contribution

It proposes a two-step user association scheme that integrates sensing and communication needs, addressing a gap in existing literature.

Findings

The proposed scheme improves spectral efficiency and sensing accuracy.

Optimizing for communication alone is not sufficient for sensing performance.

Simulation results validate the effectiveness of the joint association method.

Abstract

The cell-free massive multiple-input multiple-output (CF-mMIMO) systems are crucial for 6G development due to their high spectral efficiency and uniform user-experienced data rates. A key aspect of CF-mMIMO is user association (UA) and optimal cluster formation. Traditional methods focusing solely on communication-related metrics fall short in this context, as sensing is becoming integral to 6G. This study delves into a framework for joint radar and communication (JRC) in CF-mMIMO systems and investigates JRC-based UA techniques. We propose a novel method to optimize UA, enhancing both communication spectral efficiency and sensing accuracy. Existing literature has not explored this dual requirement integration for UA. Our proposed two-step scheme optimizes UA clusters for both communication and sensing. The first step involves selecting access points (APs) based on channel quality, followed by a second step that further refines the selection by choosing APs from the initial group that are also optimal for sensing. We utilize the signal-clutter plus noise ratio to exclude APs with clutter in front of the user equipment (UE) and the AP view angle, ensuring that radar echoes are received only from the specific UE, not the surrounding clutter. Theoretical analysis and simulations demonstrate that the same APs optimized for communication are not necessarily optimal for sensing, highlighting the need for schemes that incorporate sensing requirements in UA. The results show the effectiveness of the proposed method, showing its potential to improve CF-mMIMO system performance in JRC scenarios.