Joint Optimization of UAV Deployment and Ground Users Clustering in Air-Ground Networks: A Hierarchical Coalition-Formation Game Approach

IF 6.9 2区 计算机科学 Q1 TELECOMMUNICATIONS
Haoran Du;Runfeng Chen;Tianyao Zhong;Zhifeng Hou;Yuli Zhang;Dianxiong Liu;Haichao Wang;Yuhua Xu
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Abstract

With the development of communication technology, uncrewed aerial vehicles (UAVs) have been widely used to enhance ground communication services. However, the limited number of UAVs and the massive data requirements of ground users (GUs) restrict information transmission in air-ground networks. To satisfy the requirements of more GUs and reduce the communication overhead of GUs, this paper investigates a joint deployment of UAVs and GUs clustering optimization for collective data acquisition in air-ground networks. In light of the problem’s complexity, this paper builds a hierarchical game, where the outer game is modeled as a UAV deployment game and the inner game is modeled as a coalition formation game. A Pareto order under resource constraints is proposed in the inner game to enable more GUs to join the coalition set. The outer game is proven to have at least one Nash equilibrium (NE), and the inner game is proven to have at least one stable coalition partition. To obtain the stable solution of the hierarchical game, a joint optimization algorithm for UAV deployment and GUs clustering based on the partial space adaptive play and best response algorithm is proposed. Specially, in light of the impact of data requirements among GUs, a GU processing sequence is designed, and the coalition merging and exchange mechanism is improved in the coalition formation algorithm. Simulation results show that the proposed algorithm performs better than traditional methods, with a performance improvement of around 10% in scenarios involving around fifty GUs.
地空网络中无人机部署与地面用户聚类的联合优化:一种分层联盟-编队博弈方法
随着通信技术的发展,无人驾驶飞行器(uav)被广泛用于增强地面通信服务。然而,有限的无人机数量和地面用户的海量数据需求制约了地空网络中的信息传输。为了满足更多GUs的需求,降低GUs的通信开销,本文研究了一种无人机和GUs联合部署的空地网络集体数据采集聚类优化方法。针对问题的复杂性,本文构建了一个分层博弈模型,其中外部博弈模型为无人机部署博弈,内部博弈模型为联盟形成博弈。在内部博弈中,提出了资源约束下的帕累托秩序,使更多的GUs加入到联盟集合中。证明了外部博弈至少有一个纳什均衡,内部博弈至少有一个稳定的联盟分区。为了得到分层博弈的稳定解,提出了一种基于部分空间自适应博弈和最佳响应算法的无人机部署和GUs聚类联合优化算法。特别针对GU之间数据需求的影响,设计了GU处理顺序,改进了联盟形成算法中的联盟合并和交换机制。仿真结果表明,该算法的性能优于传统方法,在50个GUs左右的场景下,性能提升约10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Green Communications and Networking
IEEE Transactions on Green Communications and Networking Computer Science-Computer Networks and Communications
CiteScore
9.30
自引率
6.20%
发文量
181
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