论文标题
使用EM算法的启用无人机网络的节能用户聚类
Energy-efficient User Clustering for UAV-enabled Wireless Networks Using EM Algorithm
论文作者
论文摘要
无人驾驶汽车（UAV）可用于提供无线连接，以支持热点中现有的基础设施或在破坏情况下替换它。尽管板载能量有限，但启用无人机的无线无线网络性能使网络性能具有多个优势。但是，资源分配问题增加了复杂性。在本文中，我们使用修改后的预期最大化（EM）算法提出了一种基于高斯混合模型（GMM）的节能用户聚类机制。该算法旨在提供初始的用户聚类和无人机部署，可以采用其他机制来进一步增强系统性能。与其他基线方法相比，提出的算法将系统的能效提高了25％，将可靠性提高了18.3％。
Unmanned Aerial Vehicles (UAVs) can be used to provide wireless connectivity to support the existing infrastructure in hot-spots or replace it in cases of destruction. UAV-enabled wireless provides several advantages in network performance due to drone small cells (DSCs) mobility despite the limited onboard energy. However, the problem of resource allocation has added complexity. In this paper, we propose an energy-efficient user clustering mechanism based on Gaussian mixture models (GMM) using a modified Expected-Maximization (EM) algorithm. The algorithm is intended to provide the initial user clustering and drone deployment upon which additional mechanisms can be employed to further enhance the system performance. The proposed algorithm improves the energy efficiency of the system by 25% and link reliability by 18.3% compared to other baseline methods.
