Multi-AP Cooperative Beamforming for Cell-Free ISAC Networks: Balancing Communication SINR and Sensing SCNR

TL;DR

This paper proposes a multi-AP cooperative beamforming method for cell-free ISAC networks that balances communication SINR and sensing SCNR, using semidefinite relaxation for efficient optimization.

Contribution

It introduces a convex optimization framework for resource allocation in distributed ISAC systems, addressing coordination complexity and conflicting objectives.

Findings

Achieves higher communication SINR and sensing SCNR than existing methods.

Transforms a non-convex problem into a convex semidefinite program for efficient solutions.

Demonstrates effectiveness through simulation results.

Abstract

Cell-free integrated sensing and communication (ISAC) systems are facing the resource allocation challenges due to the deployment of access points (APs) and conflicting beamforming requirements between the communication and sensing functions. Unlike traditional ISAC architectures, the geographic distribution of APs introduces coordination complexity and resource-sharing conflicts that existing single-objective methods cannot adequately address. To address this challenge, we formulate an optimization problem for multi-AP cooperative beamforming that maximizes the sensing signal-to-clutter-plus-noise ratio (SCNR) under the communication rate constraints. The non-convex quadratically constrained quadratic program is transformed into a tractable convex semidefinite program via semidefinite relaxation, enabling efficient polynomial-time solutions and overcoming the local convergence limitations of traditional alternating optimization approaches. Simulation results demonstrate that the proposed approach achieves superior performance in both communication signal-to-interference-plus-noise ratio (SINR) and SCNR compared to existing schemes, confirming its effectiveness for balancing dual-functional objectives.