Clutter-Aware Target Detection for ISAC in a Millimeter-Wave Cell-Free Massive MIMO System

TL;DR

This paper explores clutter-aware target detection in a millimeter-wave cell-free massive MIMO system with integrated sensing and communication, proposing an optimization algorithm that improves detection probability by managing clutter effects.

Contribution

It introduces a novel algorithm that optimizes power and RIS phase shifts considering clutter, enhancing target detection in ISAC systems with limited LoS path knowledge.

Findings

Exploiting clutter subspace improves detection probability.

Increasing transmit clusters can impair detection performance.

Dedicated sensing streams yield significant performance gains.

Abstract

In this paper, we investigate the performance of an integrated sensing and communication (ISAC) system within a cell-free massive multiple-input multiple-output (MIMO) system. Each access point (AP) operates in the millimeter-wave (mmWave) frequency band. The APs jointly serve the user equipments (UEs) in the downlink while simultaneously detecting a target through dedicated sensing beams, which are directed toward a reconfigurable intelligent surface (RIS). Although the AP-RIS, RIS-target, and AP-target channels have both line-of-sight (LoS) and non-line-of-sight (NLoS) parts, it is assumed only knowledge of the LoS paths is available. A key contribution of this study is the consideration of clutter, which degrades the target detection if not handled. We propose an algorithm to alternatively optimize the transmit power allocation and the RIS phase-shift matrix, maximizing the target signal-to-clutter-plus-noise ratio (SCNR) while ensuring a minimum signal-to-interference-plus-noise ratio (SINR) for the UEs. Numerical results demonstrate that exploiting clutter subspace significantly enhances detection probability, particularly at high clutter-to-noise ratios, and reveal that an increased number of transmit side clusters impair detection performance. Finally, we highlight the performance gains achieved using a dedicated sensing stream.