Beamforming Tradeoff for Sensing and Communication in Cell-Free MIMO

TL;DR

This paper introduces a globally optimal, SDR-based beamforming framework for joint sensing and communication in cell-free MIMO systems, enhancing efficiency and providing a benchmark for future wireless network designs.

Contribution

It proposes a novel SDR-based optimization method that guarantees global optimality for joint beamforming in CF-MIMO, surpassing prior approaches that lacked such guarantees.

Findings

The SDR-based method achieves globally optimal beamforming solutions.

A standalone beamforming strategy benchmarks performance for dedicated sensing or communication.

The framework is computationally efficient and adaptable to multi-user scenarios.

Abstract

This paper studies optimal joint beamforming (BF) for joint sensing and communication (JSAC) in small-scale cell-free MIMO (CF-MIMO) systems. While prior works have explored JSAC optimization using methods such as successive convex approximation (SCA) and semidefinite relaxation (SDR), many of these approaches either lack global optimality or require additional rank-reduction steps. In contrast, we propose an SDR-based optimization framework that guarantees globally optimal solutions without post-processing. To benchmark its performance, we introduce a standalone BF strategy that dedicates each access point (AP) exclusively to either communication or sensing. The proposed formulation builds upon a general multi-user system model, enabling future extensions beyond the single-user setting. Overall, our framework offers a globally optimal and computationally efficient BF design, providing valuable insights for the development of next-generation wireless networks.