Proposed framework improves uplink communication through trajectory and phase optimization, indicating enhanced performance in wireless sensor networks.
Intelligent reflecting surface assisted unmanned aerial vehicles (IRS-UAVs) have been widely applied in various communication scenarios. This paper addressed the uplink communication problem in wireless sensor networks (WSN) by proposing a novel double IRS-UAVs assisted framework to improve the pairwise sum rate. Specifically, the base station (BS) received signals to users at a relatively short distance through a single-reflection link of one IRS, and received signals to users at a relatively long distance through the double-reflection link of two IRSs. Within each work cycle, the IRS-UAVs followed a fixed service sequence to cyclically assist all sensor node pairs. We designed a joint optimization algorithm that simultaneously optimized the UAV trajectories and IRS phase shifts to maximize the pairwise sum rate, while guaranteeing each node’s transmission rate meets a minimum quality of service (QoS) constraint. The proposed algorithm decomposed the optimization problem into multiple sub-problems and conducted iterative optimization, leading to the derivation of the optimal solution. Numerical results indicate that this algorithm can effectively optimize flight trajectories of the UAVs and significantly enhance the pairwise sum rate of the system.
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Zou et al. (2025) studied this question.
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