Optimized Detection with Analog Beamforming for Monostatic Integrated Sensing and Communication

TL;DR

This paper addresses detection-optimized analog beamforming for monostatic ISAC under analog-domain self-interference. It develops semidefinite relaxations to approximate detection-optimal transmit and receive beamformers and introduces a superiorized projection algorithm to solve them efficiently, while enforcing SI suppression and communication constraints. Numerical results at 28 GHz show substantial SI suppression (below $-60$ dB) and improved target-detection performance over a baseline minimization method, confirming the practical benefits of the approach. Overall, the work enables compact, cost-efficient ISAC systems by jointly balancing sensing and communication requirements through advanced projection-based optimization in the analog domain.

Abstract

In this paper, we formalize an optimization framework for analog beamforming in the context of monostatic integrated sensing and communication (ISAC), where we also address the problem of self-interference in the analog domain. As a result, we derive semidefinite programs to approach detection-optimal transmit and receive beamformers, and we devise a superiorized iterative projection algorithm to approximate them. Our simulations show that this approach outperforms the detection performance of well-known design techniques for ISAC beamforming, while it achieves satisfactory self-interference suppression.

Figures (3)

• Figure 1: System model of a monostatic transceiver with analog beamforming.
• Figure 2: roc curves with $r_{q_{\star}}=\text{20m}$ and unprobed target $q'$.
• Figure :