论文标题

无人用的协同合作与认知NOMA:部署,聚类和资源分配

UAV-Assisted Cooperative & Cognitive NOMA: Deployment, Clustering, and Resource Allocation

论文作者

Arzykulov, Sultangali, Celik, Abdulkadir, Nauryzbayev, Galymzhan, Eltawil, Ahmed M.

论文摘要

合作和认知非正交多访问(CCR-NOMA)已被认为是一种有前途的技术,可以克服频谱稀缺问题并支持下一代无线网络中设想的大规模连通性。在本文中,我们调查了无人驾驶飞机(UAV)的部署,作为接力赛,该中继为热点地区的大量二级用户提供服务。 UAV部署算法必须共同考虑用户聚类,渠道分配和资源分配子问题。我们提出了一种解决方案方法,该方法基于给定无人机位置的最佳资源分配获得用户聚类和渠道分配。为此,我们得出了封闭形式的最佳功率和时间分配,并表明它通过比几何编程所消耗的能量和时间更少,从而提供了最佳的Max-Min Fair吞吐量。基于最佳资源分配,最佳覆盖率概率还以封闭形式提供,该封闭形式将频道估计错误,硬件障碍和主要网络干扰考虑。最佳的覆盖概率由建议的Max-Min Fair用户聚类和渠道分配方法使用。结果表明,所提出的方法在比最佳基准的时间少的五个数量级以上的时间范围内达到100%的准确性。

Cooperative and cognitive non-orthogonal multiple access (CCR-NOMA) has been recognized as a promising technique to overcome issues of spectrum scarcity and support massive connectivity envisioned in next-generation wireless networks. In this paper, we investigate the deployment of an unmanned aerial vehicle (UAV) as a relay that fairly serves a large number of secondary users in a hot-spot region. The UAV deployment algorithm must jointly account for user clustering, channel assignment, and resource allocation sub-problems. We propose a solution methodology that obtains user clustering and channel assignment based on the optimal resource allocations for a given UAV location. To this end, we derive closed-form optimal power and time allocations and show it delivers optimal max-min fair throughput by consuming less energy and time than geometric programming. Based on optimal resource allocation, the optimal coverage probability is also provided in closed-form, which takes channel estimation errors, hardware impairments, and primary network interference into account. The optimal coverage probabilities are used by the proposed max-min fair user clustering and channel assignment approaches. The results show that the proposed method achieves 100% accuracy in more than five orders of magnitude less time than the optimal benchmark.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源