STAR-RIS Enabled ISAC Systems With RSMA: Joint Rate Splitting and Beamforming Optimization
This paper delves into an integrated sensing and communication (ISAC) system bolstered by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Within this system, a base station (BS) is equipped with communication and radar capabilities, enabling it to communicate with ground terminals (GTs) and concurrently probe for echo signals from a target of interest. Moreover, to manage interference and improve communication quality, the rate splitting multiple access (RSMA) scheme is incorporated into the system. The signal-to-interference-plus-noise ratio (SINR) of the received sensing echo signals is a measure of sensing performance. We formulate a joint optimization problem of common rates, transmit beamforming at the BS, and passive beamforming vectors of the STAR-RIS. The objective is to maximize sensing SINR while guaranteeing the communication rate requirements for each GT. We present an iterative algorithm to address the non-convex problem by invoking Dinkelbach’s transform, semidefinite relaxation (SDR), majorization-minimization, and sequential rank-one constraint relaxation (SROCR) theories. Simulation results manifest that the performance of the studied ISAC network enhanced by the STAR-RIS and RSMA surpasses other benchmarks considerably. The results evidently indicate the superior performance improvement of the ISAC system with the proposed RSMA-based transmission strategy design and the dynamic optimization of both transmission and reflection beamforming at STAR-RIS.
Authors
- Zesong Fei (ORCID: https://orcid.org/0000-0002-7576-625X)
- Yongdong Zhu (ORCID: https://orcid.org/0000-0002-5420-7926)
- Ruihong Jiang (ORCID: https://orcid.org/0009-0008-8523-6448)
- Ruichen Zhang (ORCID: https://orcid.org/0000-0002-6859-3645)
- Qiang Ni (ORCID: https://orcid.org/0000-0002-4593-1656)
- Dusit Niyato (ORCID: https://orcid.org/0000-0002-7442-7416)
- Huimin Hu (ORCID: https://orcid.org/0000-0002-1023-8237)
- Yuan Liu
Institutions
- Beijing Institute of Technology (CN)
- Beijing University of Posts and Telecommunications (CN)
- Nanyang Technological University (SG)
- Zhejiang Lab (CN)
- Cambridge Mechatronics (United Kingdom) (GB)
- Xi’an University of Posts and Telecommunications (CN)
- Lancaster University (GB)
Publication Details
- Journal
- IEEE Transactions on Cognitive Communications and Networking
- Published
- 2025-04-04
- DOI
- https://doi.org/10.1109/tccn.2025.3558016
- Citations
- 10
- Primary Topic
- Underwater Vehicles and Communication Systems
- Type
- article
- Field-Weighted Citation Impact
- 11.45
Funders
- National Natural Science Foundation of China