Robust Anti-Jamming Technique for UAV Data Collection in IoT Using Landing Platforms and RIS

Adopting Unmanned Aerial Vehicles (UAVs) in wireless networks provides promising methods to extend the coverage of the network. However, the uplink communications between the ground devices and the UAV are vulnerable to jamming. Although many works have exploited the maneuverability of the UAV to avoid the jammer, the UAV will not be effective when the jammer is impacting a large area. In this paper, the data collection problem in Internet of Things (IoT) using a UAV in the presence of a meliaceous jammer is investigated. A Reconfigurable Intelligent Surfaces (RIS) is adopted to help the ground IoT devices in reflecting their signals toward the UAV. Moreover, a novel network element, called Landing Platform (LP), is introduced to support a resilient data collection in the presence of high jamming power using network cables. A joint IoT devices clustering and UAV's trajectory planning is considered, where the problem is formulated mathematically. Then, the Ant Colony-based Algorithm for Joint Anti-jamming UAV Routing and IoT Devices Clustering (AC-JRC) is introduced to solve the optimization problem in an efficient way. Finally, the impact of the LPs and the performance of AC-JRC algorithm compared with other benchmarks is investigated. The objective is to minimize the weighted sum of the UAV's total traveled distance and the number of used LPs. It is shown that the solution of AC-JRC is within 9% of the optimal solution. Moreover, the AC-JRC algorithm can provide a solution better than the solutions of AC-kmeans and ACS algorithms by 17% and 61%, respectively.