Optimizing Rate-CRB Performance for Beyond Diagonal Reconfigurable Intelligent Surface Enabled ISAC

2025-08-15

AI Summary

This work addresses the joint optimization of base station beamforming and BD-RIS scattering matrix in BD-RIS-aided integrated sensing and communication (ISAC) systems, aiming to maximize the sum rate under constraints on the Cramér–Rao bound (CRB) for target localization and unitary structure of the scattering matrix. It introduces, for the first time, beyond-diagonal reconfigurable intelligent surfaces (BD-RIS) into the ISAC framework and formulates the problem as a constrained manifold optimization over the unitary group. To tackle the non-convex, coupled unitary constraints, a Riemannian steepest ascent algorithm based on a logarithmic barrier function is proposed. Simulation results demonstrate that the proposed method achieves a superior trade-off between communication rate and localization accuracy, significantly outperforming conventional diagonal RIS-based schemes. This validates the potential of BD-RIS to enhance the synergy between sensing and communication performance in ISAC systems.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Learning & Optimization for ROB

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Security and Privacy: Large-scale security measurements

Abstract

This letter considers a beyond diagonal reconfigurable intelligent surface (BD-RIS) aided integrated sensing and communication (ISAC) system, where the BD-RIS can help a multi-antenna base station (BS) serve multiple user equipments (UEs) and localize a target simultaneously. We formulate an optimization problem that designs the BS beamforming matrix and the BD-RIS scattering matrix to maximize UEs' sum rate subject to a localization Cramer-Rao bound (CRB) constraint and an additional unitary matrix constraint for the scattering matrix. Because unitary matrices form a manifold, our problem belongs to constrained manifold optimization. This letter proposes a log-barrier based Riemannian steepest ascent method to solve this problem effectively. Numerical results verify the effectiveness of our algorithm and the performance gain of the BD-RIS aided ISAC systems over the conventional RIS aided ISAC systems.

Problem

• Optimizing BD-RIS for ISAC systems with rate and localization constraints
• Designing beamforming and scattering matrices under CRB and unitary constraints
• Solving constrained manifold optimization for improved ISAC performance

Innovation

• Riemannian steepest ascent method
• BD-RIS scattering matrix optimization
• Constrained manifold optimization approach