Integrated Sensing and Communication for UAV Trajectory Optimization in Mixed FSO-RF Networks in Dynamic Weather Conditions

Integrated sensing and communication (ISAC) is expected to transform data transmission and real-time sensing, enhancing sixth-generation (6G) networks. Free-space optical (FSO) communication is a key 6G backhaul solution, complementing radio frequency (RF) technologies like millimeter wave (mmWave) for improved network reliability. However, adverse weather can significantly reduce FSO link reliability due to atmospheric attenuation. Such adverse weather conditions also increase the level of back-scattered light, potentially enabling the real-time sensing of the atmospheric channel gain at the transmitter side. Therefore, this paper proposes a novel optical ISAC (O-ISAC) framework, where the back-scattered light from the FSO communication signal is used as the sensing feedback signal. This O-ISAC framework is analyzed considering a single-cell network aided by an unmanned aerial vehicle (UAV) to support edge users. The UAV is connected to the gateway via a FSO backhaul link while estimating the FSO channel gain based on the back-scattered light and dynamically optimizing its trajectory. The aim of this adaptive O-ISAC system is to maximize the end-to-end network throughput of the edge users while considering FSO backhaul capacity and the UAV's directional antenna beamwidth and bandwidth allocation. Numerical results demonstrate that UAV can effectively optimize its trajectory by adjusting the antenna beamwidth and downlink bandwidth allocation at different weather conditions. The proposed framework is tested using hourly visibility data from Edinburgh, demonstrating that optical channel sensing is crucial for the system's overall performance.