Abstract : In recent years, symbiotic radio systems have garnered significant attention from academia and industry for addressing the challenges of spectrum scarcity and energy consumption in large-scale Internet of Things (IoT) deployments. At the same time, due to the wide distribution of IoT devices, some remote areas cannot be covered by mobile networks. Introducing unmanned aerial vehicles (UAV) into wireless networks can improve network coverage performance and increase spectrum utilization. Therefore, this paper proposes a joint optimization algorithm for channel allocation, reflection coefficients and UAV’s position for a UAV-assisted symbiotic radio system consisting of multiple primary users (PUs) and multiple backscatter devices (BDs). Under the constraints of energy and the quality of service (QoS) of the primary transmission system, the optimization problem of sum rate maximization in the backscatter communication system is constructed. The Kuhn-Munkres (KM) algorithm is used to solve the channel optimal matching problem. Based on the block coordinate descent (BCD) algorithm, the non-convex problem is decomposed into three sub-problems: transmission power, BDs’ reflection coefficients and UAV’s position. The transmission power subproblem is solved in two cases where the number of BDs is less than/greater than the number of PUs, and the expression of the optimal solution of the reflection coefficient is derived. The Nelder-Mead algorithm is used to solve the UAV’s position subproblem. Finally, the global optimal solution is obtained through global iteration. Simulation results demonstrate that the proposed algorithm achieves strong convergence and significantly enhances the sum rate of backscatter communication in UAV-assisted symbiotic radio systems.
Index terms : backscatter communication, unmanned aerial vehicle, symbiotic radio, channel allocation