RSMA-Enabled RIS-Assisted Integrated Sensing and Communication for 6G: A Comprehensive Survey

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Abstract
The evolution toward 6G wireless networks demands communication systems that are highly efficient, intelligent, and perceptive of their environment. Rate-splitting multiple access (RSMA), reconfigurable intelligent surface (RIS), and integrated sensing and communication (ISAC) have emerged as transformative technologies to meet these requirements. RSMA provides a new way to flexibly manage interference, RIS provides a controllable wireless environment, and ISAC improves spectral, energy, and hardware efficiencies. This survey presents a comprehensive study of RSMA-enabled RIS-assisted ISAC systems, covering the fundamental principles of RSMA and RIS, performance metrics, and optimization techniques.We also explore how their integration can markedly improve the performance of future wireless networks. The survey provides a comparative performance analysis with non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) under various environmental setups and practical constraints. In particular, the paper studies 20 articles on RSMA-based RIS-assisted ISAC systems, where RSMA consistently demonstrates superior performance in terms of spectral efficiency, energy efficiency, and sensing accuracy compared to NOMA and SDMA. Additionally, we examine the role of artificial intelligence (AI) and machine learning (ML) in addressing the non-convex optimization challenges of RSMA-enabled RIS-assisted ISAC systems, emphasizing the potential of generative AI, deep reinforcement learning, and quantum machine learning. The survey outlines open research problems related to hardware impairments and security and identifies promising research directions, including integration with enabling 6G technologies. This survey serves as a comprehensive reference for researchers and professionals aiming to design intelligent, secure, and adaptive 6G wireless networks empowered by RSMA-enabled RIS-assisted ISAC systems.

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