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三维无人机自组织网络两种覆盖布局总信道容量研究。

Research on the Total Channel Capacities Pertaining to Two Coverage Layouts for Three-Dimensional, UAV-Assisted Ad Hoc Networks.

机构信息

School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China.

Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu 611731, China.

出版信息

Sensors (Basel). 2023 Mar 27;23(7):3504. doi: 10.3390/s23073504.

Abstract

Unmanned aerial vehicles (UAVs) employed as airborne base stations (BSs) are considered the essential components in future sixth-generation wireless networks due to their mobility and line-of-sight communication links. For a UAV-assisted ad hoc network, its total channel capacity is greatly influenced by the deployment of UAV-BSs and the corresponding coverage layouts, where square and hexagonal cells are partitioned to divide the zones individual UAVs should serve. In this paper, the total channel capacities of these two kinds of coverage layouts are evaluated using our proposed novel computationally efficient channel capacity estimation scheme. The mean distance (MD) between a UAV-BS in the network and its served users as well as the MD from these users to the neighboring UAV-BSs are incorporated into the estimation of the achievable total channel capacity. We can significantly reduce the computational complexity by using a new polygon division strategy. The simulation results demonstrate that the square cell coverage layout can always lead to a superior channel capacity (with an average increase of 7.67% to be precise) to the hexagonal cell coverage layout for UAV-assisted ad hoc networks.

摘要

无人机(UAV)作为空中基站(BS)被认为是未来六代无线网络的重要组成部分,因为它们具有移动性和视距通信链路。对于无人机辅助的自组织网络,其总信道容量受无人机-BS 的部署和相应的覆盖布局影响很大,其中将正方形和六边形小区划分以划分各个无人机应服务的区域。在本文中,我们使用提出的新颖的计算有效的信道容量估计方案来评估这两种覆盖布局的总信道容量。网络中无人机-BS 与其服务用户之间的平均距离(MD)以及这些用户到相邻无人机-BS 的 MD 都被纳入可实现总信道容量的估计中。通过使用新的多边形划分策略,我们可以显著降低计算复杂度。仿真结果表明,对于无人机辅助的自组织网络,正方形小区覆盖布局始终可以提供更高的信道容量(平均增加 7.67%),而六边形小区覆盖布局则无法实现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdf1/10099046/a64e8d63f1fc/sensors-23-03504-g001.jpg

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