Energy Efficient Beamforming Optimization for Integrated On-Demand Sensing and Communication in High-Speed Railway Mobile Networks

The introduction of Integrated Sensing and Communication (ISAC) technology in high-speed railway mobile networks (HSRMNs) addresses reliability concerns within existing railway operation control systems. However, current ISAC research often focuses on overall performance assessment across extended periods, potentially overlooking practical sensing requirements, resulting in degraded or even unstable communication performance. To mitigate these challenges, we propose an Integrated On-Demand Sensing and Communication (IDSAC) mechanism for HSRMNs. IDSAC optimizes train communication energy efficiency (EE) by jointly optimizing target sensing selection and transmit beamforming, while adhering to Age of Information (AoI) constraints and ensuring beam pattern gain for designated targets. To tackle the non-convex mixed-integer programming challenge, we decompose the problem into two parts. First, we employ iterative algorithms using successive convex approximation (SCA) and semidefinite relaxation (SDR) to address the EE problem. Second, we introduce a dynamic control algorithm employing the Lyapunov drift-plus-penalty method to manage AoI constraints and sensing selection. Our joint optimization approach achieves optimal EE under dynamic operational constraints typical of high-speed rail systems. Simulation results validate the effectiveness of IDSAC in optimizing ISAC performance, enhancing railway safety and communication efficiency.