Interference Management in MIMO-ISAC Systems: A Transceiver Design Approach

TL;DR

This paper presents a joint optimization framework for MIMO-ISAC systems that enhances interference management by designing transmit and receive strategies to maximize sensing and communication performance simultaneously.

Contribution

It introduces a novel transceiver design approach using quadratic transformation and covariance matrix tapers to improve robustness and efficiency in interference management for MIMO-ISAC systems.

Findings

The proposed algorithm improves SCNR in simulations.

Robustness is enhanced through covariance matrix tapers.

The framework effectively balances sensing and communication requirements.

Abstract

The integrated sensing and communication (ISAC) system under multi-input multi-output (MIMO) architecture achieves dual functionalities of sensing and communication on the same platform by utilizing spatial gain, which provides a feasible paradigm facing spectrum congestion. However, the dual functionalities of sensing and communication operating simultaneously in the same platform bring severe interference in the ISAC systems. Facing this challenge, we propose a joint optimization framework for transmit beamforming and receive filter design for ISAC systems with MIMO architecture. We aim to maximize the signal-to-clutter-plus-noise ratio (SCNR) at the receiver while considering various constraints such as waveform similarity, power budget, and communication performance requirements to ensure the integration of the dual functionalities. In particular, the overall transmit beamforming is refined into sensing beamforming and communication beamforming, and a quadratic transformation (QT) is introduced to relax and convert the complex non-convex optimization objective. An efficient algorithm based on covariance matrix tapers (CMT) is proposed to restructure the clutter covariance matrix considering the mismatched steering vector, thereby improving the robustness of the ISAC transceiver design. Numerical simulations are provided to demonstrate the effectiveness of the proposed algorithm.