Beamforming method for communication and sensing system based on super-diagonal reconfigurable intelligent metasurface

CN122372026APending Publication Date: 2026-07-10NORTHWESTERN POLYTECHNICAL UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NORTHWESTERN POLYTECHNICAL UNIV
Filing Date
2026-05-13
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing RIS architectures are typically single-connected, which limits performance enhancements. Furthermore, the potential of BD-RIS in reflection mode for more general transport or hybrid reflection transport modes has not been fully explored, making it difficult to achieve full-space service and communication-aware performance improvements.

Method used

Deploy a BD-RIS-assisted ISAC system, optimize the base station beamforming matrix, BD-RIS reflection matrix, and transmission matrix, and achieve a combination of reflection space sensing and transmission space communication through Riemannian manifold optimization through alternating iterations. This system is suitable for both cooperative and non-cooperative targets.

Benefits of technology

Without requiring prior information about the target, the ISAC system improves perception performance and spatial coverage, and is applicable to both cooperative and non-cooperative targets. Compared to the traditional STAR-RIS scheme, it can effectively improve CRB performance by 36.8%.

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Abstract

This invention discloses a beamforming method for a communication sensing system based on a superdiagonal reconfigurable smart metasurface. First, a BD-RIS-assisted ISAC system is deployed. Then, a sensing performance optimization problem for the BD-RIS-assisted ISAC system is constructed, optimizing the base station beamforming matrix, BD-RIS reflection matrix, and transmission matrix. Next, the base station beamforming matrix and BD-RIS matrix are initialized, setting the maximum number of iterations and convergence accuracy. The BD-RIS reflection and transmission matrices are fixed, and Riemannian manifold optimization is used to solve the base station beamforming matrix. The base station beamforming matrix is ​​fixed again, and Riemannian manifold optimization is used to solve the BD-RIS reflection and transmission matrices. Finally, the base station beamforming matrix and the BD-RIS reflection and transmission matrices are iteratively optimized alternately until the CRB error value is less than a threshold or the maximum number of iterations is reached. This invention utilizes the characteristics of BD-RIS to complete both reflection space sensing and transmission space communication tasks, without requiring any prior information about the sensing target, and is applicable to both cooperative and non-cooperative scenarios.
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