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Multi-UAV Interference Coordination via Joint Trajectory and Power Control
IEEE Transactions on Signal Processing ( IF 5.230 ) Pub Date : 2020-01-16 , DOI: 10.1109/tsp.2020.2967146
Chao Shen; Tsung-Hui Chang; Jie Gong; Yong Zeng; Rui Zhang

Recently, unmanned aerial vehicles (UAVs) have found growing applications in wireless communications and sensor networks. One of the key challenges for UAV-based wireless networks lies in managing the strong cross-link interference caused by the line-of-sight dominated propagation conditions. In this article, we address this challenge by studying a UAV-enabled interference channel (UAV-IC), where each of the $K$ UAVs communicates with its associated ground terminal. To exploit the new degree of freedom of UAV mobility, we formulate a joint trajectory and power control (TPC) problem for maximizing the aggregate sum rate of the UAV-IC for a given flight interval, under practical constraints on the UAV flying speed, altitude, and collision avoidance. These constraints couple the TPC variables across different time slots and UAVs, leading to a challenging large-scale and non-convex optimization problem. We show that the optimal TPC solution follows the fly--hover--fly strategy, based on which the problem can be handled first by finding optimal hovering locations followed by solving a dimension-reduced TPC problem. For the reduced TPC problem, we propose a successive convex approximation algorithm. To further reduce the computation time, we develop a parallel TPC algorithm that is efficiently implementable over multi-core CPUs. We also propose a segment-by-segment method that decomposes the TPC problem into sequential TPC subproblems each with a smaller problem dimension. Simulation results demonstrate the superior computation time efficiency of the proposed algorithms, and also show that the UAV-IC can yield higher network sum rate than the benchmark orthogonal schemes.
更新日期:2020-02-11

 

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