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

TL;DR

The paper tackles robust transceiver design for RIS-enhanced DFRC systems employing movable antennas under imperfect sensing and communication channels. It introduces a convex-hull based transformation to handle continuous sensing-uncertainty regions and develops a two-layer BCD algorithm that blends FP, SCA, S-Lemma, and penalty techniques to produce SDP subproblems. The approach yields significant improvements in minimum radar SINR while achieving a balanced DASH between radar and communications, with convergence guarantees and complexity analysis. A perfect-CSI upper bound is provided for reference, and extensive simulations validate robustness to channel uncertainties and the benefits of MA and RIS in enhancing sensing coverage. The work lays a foundation for scalable, robust MA-RIS-DFRC designs and points to future exploration of statistical CSI and antenna-placement uncertainties.

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.

Figures (10)

• Figure 1: The RIS-enhanced DFRC system with movable antennas.
• Figure 2: Convergence behaviour of the two-layer BCD method.
• Figure 3: The minimum radar SINR of different schemes versus transmission power $P_t$.
• Figure 4: The minimum radar SINR of different channel uncertainty levels versus transmission power $P_t$.
• Figure 5: The minimum radar SINR versus the normalized moving region.