Non-position-based UAV trajectory optimization for coverage maximization

Ye Jiang, D. Zhai, Mengke Yang, Zheng Lin, Yuanzhan Li
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Abstract

In modern communication network, terrestrial base stations (TBSs) are difficult to achieve full coverage of the users in remote areas. As a potential solution, unmanned aerial vehicle (UAV) can assist TBSs to enhance coverage, owing to its mobility and flexibility. In this paper, we concentrate on the UAV trajectory optimization problem for further upgrading network coverage ratio. The scenarios of static and mobile users are considered respectively, where UAV trajectory needs to be optimized to achieve maximum coverage of users. In view of the complexity of user movement, we cannot find users' positions easily with traditional convex optimization ways. Therefore, we propose a DQN-based trajectory optimization algorithm, which can obtain the optimized UAV trajectory, and then achieve maximize the coverage of users. According to the simulation results, we find that the proposed algorithm improves the coverage ratio and is better than the random method in both static and mobile scenarios.
覆盖最大化的非基于位置的无人机轨迹优化
在现代通信网络中,地面基站难以实现对偏远地区用户的全覆盖。作为一种潜在的解决方案,无人机(UAV)由于其机动性和灵活性可以帮助tss增强覆盖范围。本文主要研究无人机的轨迹优化问题,以进一步提高网络覆盖率。分别考虑静态用户和移动用户两种场景,需要对无人机轨迹进行优化,实现对用户的最大覆盖。考虑到用户移动的复杂性,传统的凸优化方法很难找到用户的位置。因此,我们提出了一种基于dqn的轨迹优化算法,该算法可以获得优化后的无人机轨迹,进而实现对用户的最大覆盖。仿真结果表明,该算法在静态和移动场景下均优于随机方法,提高了覆盖率。
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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