Detecting Unauthorized Drones with Cell-Free Integrated Sensing and Communication

Sammanfattning

In recent developments in cell-free massive multiple-input multiple-output (MIMO) systems, integrated sensing and communication (ISAC) technology has shown great potential by enhancing network efficiency through the dual use of resources for both communication and sensing applications. This project introduces a cell-free massive MIMO-ISAC framework aimed at detecting unauthorized drones while simultaneously meeting communication requirements. A Maximum a Posteriori Ratio Test (MAPRT) detector is proposed to identify passive aerial targets by processing signals received from distributed ground-based access points (RX-APs). Alongside sensing accuracy, timeliness is critical, as targets may exit the area before the sensing process is completed. To assess sensing performance, we define age of sensing (AoS) and sensing coverage as our performance metrics. We propose a joint blocklength and power optimization algorithm to jointly minimize AoS and maximize sensing coverage while ensuring communication requirements are met. Additionally, an adaptive weight selection algorithm is designed to balance AoS and sensing coverage. Simulation results show that, as communication demand increases, sensing coverage decreases while AoS increases. However, the proposed algorithm achieves almost full sensing coverage while reducing AoS by 45% compared to fixed-weight approaches in power and blocklength allocation.