On Low-Complexity Transmit Beamforming for Distributed ISAC Systems

In this paper, we consider transmit beamforming in distributed integrated sensing and communication (ISAC) systems with large arrays. We propose generalized sparse coordinated multipoint transmission (GS-CoMP), a novel coordination strategy that serves a carefully selected subset of UEs while simultaneously sensing targets. Our approach designs sparse transmit precoders to ensure desired communication and sensing signal-to-interference-plus-noise ratios (SINRs), balancing backhaul rate and transmit power requirements. We focus on both unstructured and line-of-sight (LoS) scenarios. For the setting with a moderate number of antennas and unstructured channels, we present a convex semidefinite programming (SDP)-based iterative solver. For large array systems with LoS channels, we introduce a low-complexity method based on power allocation and spatial window design. Numerical simulations show that GS-CoMP significantly reduces transmit power compared to limited cooperation schemes while requiring a much lower backhaul rate than fully cooperative DISAC systems. Additionally, the proposed low-complexity methods achieve performance comparable to full SDP-based precoding with several orders of magnitude reduction in runtime.