Optimizing Secure Multi-User ISAC Systems With STAR-RIS: A Deep Reinforcement Learning Approach for 6G Networks
Southeast University · Al-Ahliyya Amman University · +3 more institutions
Abstract
The rapid evolution of wireless communication technologies and the increasing demand for multi-functional systems have led to the emergence of integrated sensing and communication (ISAC) as a key enabler for future 6G networks. Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently garnered significant attention for their ability to enhance signal coverage and improve system efficiency. This paper investigates a STAR-RIS-assisted ISAC system designed to secure communication for multiple legitimate users (LUs) while safeguarding against multiple eavesdroppers (Eves). By jointly optimizing the base station (BS) transmit beamforming, STAR-RIS transmission and…
Citation impact
- FWCI
- 83.78
- Percentile
- 100%
- References
- 31
Authors
6Topics & keywords
- Reinforcement learning
- Computer science
- Star (game theory)
- Human–computer interaction
- Artificial intelligence
- Astrophysics
- Physics