多无人机辅助通信网络中eMBB和URLLC业务的蜂窝卸载

Y. Prathyusha, T. Sheu
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引用次数: 0

摘要

随着无线蜂窝技术的出现和蜂窝基础设施的密集部署,将无人机(uav)纳入第五代(5G)及以后的网络是一种有前途的解决方案,可以支持广泛的多样化应用。5G无线系统旨在支持两种有前景的关键服务:增强型移动宽带(eMBB)和超可靠低延迟通信(URLLC)。本文以非正交多址(NOMA)下多无人机的吞吐量最大化为目标,研究了eMBB和URLLC业务的资源分配问题。首先,对于无人机的部署,我们采用基于K-means的聚类算法进行用户划分。在此基础上,提出了一种简单、低复杂度的资源分配算法。采用系统性能指标方面的数值模拟来评估所提出的方法相对于基线方法的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cellular Offloading of eMBB and URLLC Services in Multiple UAV-aided Communication Networks
With the emergence of wireless cellular technologies and the dense deployment of cellular infrastructure, incorporating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and beyond networks is a promising solution to support a wide range of diversified applications. The 5G wireless systems are intended to support two promising critical services: enhanced mobile broadband (eMBB) and ultra-reliable and low latency communications (URLLC). In this paper, we studied the resource allocation problem of eMBB and URLLC services with the aim of maximizing throughput under non-orthogonal multiple access (NOMA) with the aid of multiple UAVs. Initially, for the deployment of UAVs, we adopted K-means based clustering algorithm for user partitioning. Then, we proposed a simple low complex algorithm for resource allocation. The significance of the proposed methodology over baseline approaches is evaluated using numerical simulations in terms of system performance indicators.
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