Research on Energy Efficiency Optimization and Path Planning for RIS-Assisted UAV Communication System

In this paper, an active reconfigurable intelligent surfaces (RIS)-assisted Unmanned aerial vehicle (UAV) communication system is constructed, and a joint optimization method for UAV trajectory and system energy efficiency is proposed. In this optimization problem, firstly, the optimization problem of the phase shift matrix of the active RIS is solved by using the successive convex approximation algorithm. The transmit power optimization problem is solved by using the improved gradient descent method; Secondly, the communication energy efficiency is taken as the cost function, and the UAV trajectory is optimized by using the improved particle swarm optimization algorithm. Simulation results show that our algorithm is feasible for improving communication energy efficiency and UAV path planning.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1145/3707292.3707368
Primary Topic
UAV Applications and Optimization
Type
article
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Research on Energy Efficiency Optimization and Path Planning for RIS-Assisted UAV Communication System

Li Wang, Shurui Fan, D. G. Zhang, Xiaoyu An et al.
UAV Applications and Optimization
article

Research on Energy Efficiency Optimization and Path Planning for RIS-Assisted UAV Communication System

Li Wang, Shurui Fan, D. G. Zhang, Xiaoyu An, Yujie Wang
article en

Abstract

In this paper, an active reconfigurable intelligent surfaces (RIS)-assisted Unmanned aerial vehicle (UAV) communication system is constructed, and a joint optimization method for UAV trajectory and system energy efficiency is proposed. In this optimization problem, firstly, the optimization problem of the phase shift matrix of the active RIS is solved by using the successive convex approximation algorithm. The transmit power optimization problem is solved by using the improved gradient descent method; Secondly, the communication energy efficiency is taken as the cost function, and the UAV trajectory is optimized by using the improved particle swarm optimization algorithm. Simulation results show that our algorithm is feasible for improving communication energy efficiency and UAV path planning.

Hebei University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 55%
UAV Applications and Optimization
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