Robust Transceiver Design for RIS Enhanced Dual-Functional Radar-Communication with Movable Antenna

TL;DR

This paper proposes a robust transceiver design for RIS-enhanced dual-functional radar-communication systems with movable antennas, jointly optimizing parameters to improve radar SINR and coverage in uncertain environments.

Contribution

It introduces a unified robust optimization framework that accounts for channel uncertainties and jointly optimizes beamforming, antenna placement, and RIS coefficients in MA-aided DFRC systems.

Findings

Significant enhancement in radar SINR performance.

Effective balancing of radar and communication functions.

Robustness against channel uncertainties demonstrated through simulations.

Abstract

Movable antennas (MAs) have demonstrated significant potential in enhancing the performance of dual-functional radar-communication (DFRC) systems. In this paper, we explore an MA-aided DFRC system that utilizes a reconfigurable intelligent surface (RIS) to enhance signal coverage for communications in dead zones. To enhance the radar sensing performance in practical DFRC environments, we propose a unified robust transceiver design framework aimed at maximizing the minimum radar signal-to-interference-plus-noise ratio (SINR) in a cluttered environment. Our approach jointly optimizes transmit beamforming, receive filtering, antenna placement, and RIS reflecting coefficients under imperfect channel state information (CSI) for both sensing and communication channels. To deal with the channel uncertainty-constrained issue, we leverage the convex hull method to transform the primal problem into a more tractable form. We then introduce a two-layer block coordinate descent (BCD) algorithm, incorporating fractional programming (FP), successive convex approximation (SCA), S-Lemma, and penalty techniques to reformulate it into a series of semidefinite program (SDP) subproblems that can be efficiently solved. We provide a comprehensive analysis of the convergence and computational complexity for the proposed design framework. Simulation results demonstrate the robustness of the proposed method, and show that the MA-based design framework can significantly enhance the radar SINR performance while achieving an effective balance between the radar and communication performance.