Integrated sensing and communication empowered by resilient massive access in SAGIN: An energy efficient perspective

As key technologies in 6G, Space-Air-Ground Integrated Networks (SAGIN) promises to provide seamless global coverage through a comprehensive, ubiquitous communication system, while Integrated Sensing and Communications (ISAC) effectively addresses spectrum congestion by sharing spectrum resources and transceivers for simultaneous communication and sensing operations. However, existing ISAC research has primarily focused on terrestrial networks, with limited exploration of its applications in SAGIN environments. This paper proposes a novel SAGIN-ISAC scheme leveraging High-Altitude Platform Stations (HAPS). In this scheme, HAPS serves as a relay node that not only amplifies and forwards communication signals but also receives and processes target echo signals for parameter estimation. The satellite employs Resilient Massive Access (RMA) to provide communication services to different User Terminals (UTs). To address scenarios with an unknown number of targets, we develop a Two-threshold Detection and Parameter Multiple Signal Classification (MUSIC) algorithm (TDPM), which employs dual-threshold correlation detection to determine the number of targets and utilizes the MUSIC algorithm to estimate targets' Angle of Arrival (AoA), range, and relative velocity. Furthermore, we establish a joint optimization framework that considers both communication and sensing performance, optimizing energy efficiency, detection probability, and the Cramér-Rao bound. The power allocation coefficients are derived through Nash equilibrium, while the precoding matrix is optimized using Sequential Convex Approximation (SCA) to address the non-convex nature of the optimization problem. Experimental results demonstrate that our proposed scheme significantly enhances the overall performance of the SAGIN-ISAC system.