On the Outage and Sensing Performance of Multi-Sector RIS-Assisted ISAC Networks

Abstract

With the arrival of sixth-generation communication systems, advanced technologies like reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), and non-orthogonal multiple access (NOMA) are poised to drive a broad range of Internet of Things (IoT) applications. Integrating ISAC into multi-input single-output (MISO) networks calls for a reassessment of performance metrics such as outage probability and sensing rate. Furthermore, a critical challenge is managing heterogeneous user deployments and dynamically adapting to varying user locations while minimizing interference. To address these challenges, this work proposes an innovative multi-sector RIS framework. By dividing the RIS into independently controlled sectors, the system dynamically selects the sector closest to each user. For downlink transmission, a dual-function base station (BS) utilizes NOMA to serve the user clusters and transmit a sensing signal. The RIS dynamically selects the sector closest to the close-proximity user based on their location. To support this, the proposed approach employs a nearest-sector selection strategy centered around a reference close-proximity user. Closed-form approximations for the outage probability are then derived, assuming a blocked direct link between the BS and the users. This framework also enables ISAC by transmitting sensing signals within the selected sector, facilitating both user communication and target detection. We characterize the sensing by the sensing rate, with results showing that increasing RIS elements in the multi-sector design enhances the sensing rate. Overall, the proposed system demonstrates superior performance over traditional simultaneously transmitting and reflecting (STAR)RIS configurations and space division multiple access (SDMA) systems. In particular, the proposed system achieves a gain of 8dB, 12dB and 2dB over SDMA, conventional RIS and STAR-RIS systems, respectively. © 2026 IEEE.