Intelligent route planning method with jointing topology control of UAV swarm

被引：0
|
作者：
Yan Z. [1 ]
Yi Z. [1 ]
Ouyang B. [1 ]
Wang Y. [1 ]
机构：
[1] College of Electrical and Information Engineering, Hunan University, Changsha
来源：
Tongxin Xuebao/Journal on Communications | 2024年 / 45卷 / 02期
基金：
中国国家自然科学基金;
关键词：
deep reinforcement learning; proximal policy optimization; routing protocol; topology control; UAV swarm;
D O I：
10.11959/j.issn.1000-436x.2024032
中图分类号：
学科分类号：
摘要：
Existing routing protocols without awareness of the topology causes excessive retransmissions, energy holes, and long delay, data routing performance was seriously deteriorated. Considering the relation of topology and routing, an intelligent route planning with jointing topology control (IRPJTC) method was proposed. IRPJTC consisted of two part, the virtual force-based adaptive topology control (VFATC), and the PPO-based geographic routing protocol (PPO-GRP). Based on neighbor’s mobility information, the distance between UAVs was adaptively adjusted by VFATC to provide stable links between UAVs. Combined with link stability metric in VFATC, end-to-end delay and energy consumption, a multi-objective reward function was designed by PPO-GRP to train optimal routing strategy. According to the performance study, the proposed IRPJTC reduces existing routing protocols by 12.11% of end-to-end delay, and 4.56% of energy consumption, and has a better energy balance ability. © 2024 Editorial Board of Journal on Communications. All rights reserved.
引用
收藏
页码：137 / 149
页数：12
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