The rapid development of network technology and the advent of various smart devices can cause the rapid growth of network data traffic in the hot areas. However, the existing cellular network capacity cannot meet the needs of network users. Therefore, the small cellular base stations (SCBSs) are proposed and widely used. Nevertheless, the physical cell identifications (PCI) are extremely limited, thus it is difficult to reasonably allocate the limited PCIs to the massive SCBSs, which greatly affect the quality of service (QoS) for users in hot areas. In this paper, a PCI allocation and reuse scheme based on the maximum degree first coloring (MDFC) algorithm is proposed to allocate the limited PCIs for SCBSs in hot areas. Moreover, the K-means clustering algorithm is adopted to divide and identify different hot areas with the mobility data of massive users, which also contributes to the allocation of PCIs. The proposed scheme reduces the rate of PCI conflict and confusion, and improves the users' QoS. Simulation results show that the MDFC algorithm has better PCI allocation efficiency, and shorter PCI allocation time. Thus, it is more suitable for the deployment of cellular networks in hot areas.

中文翻译：

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基于最大度优先着色算法的物理细胞识别分配与重用方案

网络技术的飞速发展和各种智能设备的出现，可能导致热点地区网络数据流量的快速增长。但是，现有的蜂窝网络容量不能满足网络用户的需求。因此，提出并广泛使用了小型蜂窝基站（SCBS）。然而，物理小区标识（PCI）非常有限，因此很难将有限的PCI合理地分配给大型SCBS，这极大地影响了热区用户的服务质量（QoS）。提出了一种基于最大优先度着色算法的PCI分配与重用方案，为热点地区的SCBS分配有限的PCI。此外，采用K-means聚类算法，利用海量用户的移动数据对不同的热点区域进行划分和识别，这也有助于PCI的分配。所提出的方案减少了PCI冲突和混乱的发生率，并提高了用户的QoS。仿真结果表明，MDFC算法具有更好的PCI分配效率和更短的PCI分配时间。因此，它更适合在炎热地区部署蜂窝网络。