无人机定位与用户设备功率分配

J. Martins, C. H. Antunes, Marco Gomes, V. Silva, R. Dinis
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引用次数: 0

摘要

在不久的将来,无人驾驶飞行器(uav)将在下一代无线通信系统中具有巨大的潜在应用,它们可以协作为多个用户设备(UE)提供通信服务。灾难场景是一个相关的研究课题,其中无人机可以在基站(BS)可能无法运行的情况下帮助建立连接。由此产生的无人机定位影响到每个无人机-终端链路的整体频谱效率(SE)。此外,由于有限的可用能量是这些设备最重要的限制之一,因此必须优化ue的能耗。因此,必须确定最低功耗,以保证灾难位置中的最低SE吞吐量。本文研究了一种针对无人机和ue的协同启发式优化算法。我们提出了两种并行优化方法:一种是无人机搜索位置过程,以找到为其预分配ue服务的最佳可能位置;另一个是为每个用户的设备找到最低可能的上行链路(UL)功率值。初步结果表明,差分进化算法在可接受的计算运行时间内得到了较好的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unmanned aerial vehicle positioning and user equipment power allocation
In the near future, unmanned aerial vehicles (UAVs) will have enormous potential applications for next generation wireless communication systems, in which they can collaborate to serve several user equipment (UE) for communication purposes.Disaster scenarios are a relevant research topic, in which UAVs can aid establishing connections in circumstances where base stations (BS) may be inoperative.The resulting UAV positioning affects the overall spectral efficiency (SE) in each UAV-UE link. Moreover, UEs energy consumption must be optimized since the finite amount of energy available is one of the most significant limitations of these devices. Therefore, it is essential to determine the lowest power consumption necessary to guarantee a minimum SE throughput in a disaster location.In this paper, we investigate a cooperative meta-heuristic (MH) optimization algorithm for both the UAVs and UEs. We propose two parallel optimization approaches: one is the UAV search position process to find the best possible location to serve its pre-allocated UEs; the other is finding the lowest possible uplink (UL) power values for each user’s equipment. The preliminary results show that the Differential Evolution (DE) algorithm reaches good quality solutions in acceptable computation runtime.
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