Optimization of Trajectory Scheduling and Time Allocation in UAV-assisted Backscatter Communication

Backscatter communication has emerged as a promising energy-conserving technology for massive devices with energy constraints and manufacturing cost, where backscatter nodes (BNs) could harvest energy from radio frequency (RF) signal for their operations. The unmanned aerial vehicle (UAV)-based wireless communication has attracted wide attention in backscattering data collection recently due to its flexible deployment and controllable mobility. However, when BNs transmit information to UAV, different data collection modes of UAVs may affect the stability of communication link and the validity of data transmission, which requires a trade-off for energy conservation. To tackle this problem, we maximize the energy efficiency (EE) of UAV-assisted backscatter communication network via jointly optimizing time resource allocation and UAV trajectory. Particularly, the target region is divided into several sub-regions via K-means based region partition approach. The optimization problem is non-convex, and an effective Dinkelbach-based iterative algorithm is adopted to derive the optimal solution. Simulation results show that the proposed algorithm has better EE performance compared to two existing baseline schemes.