Distributed Hybrid Beamforming Design for Cooperative Cell-Free Integrated Sensing and Communication Networks

This paper proposes a cooperative cell-free integrated sensing and communication network (CoCF-ISACNet) adopting hybrid beamforming (HBF) architecture, which improves both radar sensing and communication performance. The main contributions of this work are three-fold. First, we introduce a CoCF-ISACNet with energy-efficient HBF architecture. To show the benefits of proposed CoCF-ISACNet, we propose to jointly design the HBF to maximize the network communication capacity while satisfying the constraint of beampattern similarity for radar sensing, which results in a highly dimensional and non-convex problem. Second, to facilitate the joint design, we propose a novel distributed optimization framework called Proximal grAdieNt Decentralized Alternating direction method of multipliers (PANDA). Third, we further adopt the proposed PANDA framework to solve the joint HBF design problem for the CoCF-ISACNet. By using the proposed PANDA framework, all access points (APs) optimize the HBF in parallel, where each AP only requires local channel state information and limited message exchange among the APs. Such framework reduces significantly the computational complexity and thus has pronounced benefits in practical scenarios. Simulation results verify the effectiveness of the proposed algorithm compared with the conventional centralized algorithm and show the remarkable performance improvement of radar sensing and communication by deploying CoCF-ISACNet.