In millimeter wave (mmWave) networks, base stations (BSs) are expected to be densely deployed in order to meet the demands of mobile users. A major challenge in dense mmWave networks is the interference experienced by the user from the neighboring BSs which limits the density of deployed BSs. A promising solution to this challenge is to adopt user-centric BS cooperation that allows a user to be connected to a set (cluster) of BSs instead of being associated with a single one. In this paper, we investigate the performance of user-centric mmWave networks with dynamic clustering. First, we propose a dynamic clustering model to enable the user-centric BS cooperation. Then, based on the proposed model, we analyze the coverage probability and average spectral efficiency (ASE) performances using stochastic geometry tools. We also propose a BS clustering optimization framework to achieve maximum ASE performance for given network configuration. Finally, numerical and simulation results are provided, showing that the proposed dynamic clustering schemes always outperform static clustering and single-BS selection schemes and yield an optimum system performance for given network parameters.

中文翻译：

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以用户为中心的毫米波网络中的动态基站集群：性能分析和优化


在毫米波（mmWave）网络中，基站（BS）预计将被密集部署，以满足移动用户的需求。密集毫米波网络的一个主要挑战是用户受到来自相邻基站的干扰，这限制了已部署基站的密度。应对这一挑战的一个有前途的解决方案是采用以用户为中心的基站协作，允许用户连接到一组（集群）基站，而不是与单个基站关联。在本文中，我们研究了具有动态集群的以用户为中心的毫米波网络的性能。首先，我们提出了一种动态聚类模型来实现以用户为中心的BS合作。然后，基于所提出的模型，我们使用随机几何工具分析覆盖概率和平均频谱效率（ASE）性能。我们还提出了 BS 集群优化框架，以在给定的网络配置下实现最大 ASE 性能。最后，提供了数值和仿真结果，表明所提出的动态聚类方案始终优于静态聚类和单基站选择方案，并针对给定的网络参数产生最佳的系统性能。