Multi-pass Cooperative Near-Field and Far-Field ISAC Energy Efficiency Optimization

Abstract

In the recent past, Pinching Antenna Systems (PASS) have gained popularity because of their flexible deployment strategies and efficient link gain performance. This study presents a novel integrated sensing and communication (ISAC) system assisted by multiple flexible RF feedlines (or tracks) and multiple active Reconfigurable Intelligent Surfaces (RIS) to optimize real-time monitoring and data transmission across automated production lines. The proposed ISAC system includes a communication energy efficiency maximization problem subject to the sensing Signal-to-Noise Ratio (SNR) and power budget constraints. The resulting optimization problem is solved by employing an alternating optimization strategy to reformulate the original problem into three tractable sub-problems: the PASS antennas optimization problem, the digital beamforming problem, and the active RIS reflection matrix problem. The three original problems are then solved by utilizing methods that involve Fractional Programming, the Penalty Function Method, and the Element-wise Optimization strategy, respectively. Simulation outcomes show a significant improvement in both energy efficiency and sensing performance for the novel strategy compared to the Multiple-Input Multiple-Output (MIMO) and the Passive RIS-Assisted PASS system. Specifically, the proposed scheme achieves up to 166.7% higher energy efficiency than the conventional MIMO-ISAC baseline under identical power budgets and interference constraints.