Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/19210
Title: Integrated ISAC-RIS Systems for Next-Generation Connectivity Enhancement
Authors: Kokare, Manojkumar B.
Sharma, Neha
Gautam, Sumit
Swaminathan, Ramabadran
Issue Date: 2026
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Kokare, M. B., Sharma, N., Gautam, S., & Swaminathan. (2026). Integrated ISAC-RIS Systems for Next-Generation Connectivity Enhancement. In Signals and Communication Technology: Part F2410. https://doi.org/10.1007/978-981-92-0209-6_2
Abstract: This chapter provides an extensive survey of recent advancements in integrated sensing and communication (ISAC) systems facilitated by reconfigurable intelligent surfaces (RIS), emphasizing their transformative potential for next-generation wireless networks. A systematic overview is presented, covering the fundamental principles, key enabling technologies, and possible state-of-the-art implementations of ISAC-RIS architectures. The dual functionality of ISAC-RIS in enhancing both sensing accuracy and communication reliability through intelligent signal manipulation and environment-aware beamforming is highlighted. A detailed taxonomy is introduced, categorizing existing works based on application domains. In this chapter, we provide a critical evaluation of different system architectures utilizing ISAC-RIS for connectivity enhancement across various use cases, including unmanned aerial vehicle (UAV) systems, vehicle-to-everything (V2X) communications, Internet-of-things (IoT) applications, and secure transmission. It also presents a simplified case study of ISAC-RIS systems, focusing on performance analysis through outage probability (OP) and exploring optimization techniques aimed at maximizing the overall sum rate. In addition, emerging trends are discussed, including the integration of simultaneous transmitting and reflecting (STAR)-RIS systems, beyond diagonal RIS, simultaneous wireless information and power transfer (SWIPT) systems for energy efficiency enhancement and aspects of machine learning (ML) for adaptive RIS configuration to improve overall system performance. The chapter concludes with a review of open research challenges and future directions, providing valuable insights for researchers at the intersection of sensing, communication, and smart radio environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
URI: https://dx.doi.org/10.1007/978-981-92-0209-6_2
https://dspace.iiti.ac.in/handle/123456789/19210
ISSN: 1860-4862
Type of Material: Book Chapter
Appears in Collections:Department of Electrical Engineering

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