不要再叫我蜂窝：无线网络中缩放定律、分形图案和小世界的出现
Not Call Me Cellular Any More: The Emergence of Scaling Law, Fractal Patterns and Small-World in Wireless Networks
摘要：
在传统的蜂窝网络中，对于彼此远离地部署的基站（BS），通常假设它们是相互独立的。然而，经过几代蜂窝网络的长期演进，这种假设不再成立。相反，似乎由运营商以面向服务的方式逐渐部署的BS在其位置、覆盖范围和业务负载中嵌入了许多根本上独特的特征。这些特征可以被用来分析BS甚至人类社区中的内在模式。本文根据大规模测量数据集，利用BS的一个重要特征，空间交通。结合复杂网络理论，进一步分析了该模型的结构和特性。数值结果表明，度分布服从无标度性质。这些数据集还揭示了分形和小世界的特征。此外，我们采用集体影响（CI）算法定位有影响力的基站，并证明一些低程度的BS可能会超过BS与更大的程度。
英文摘要：
In conventional cellular networks, for base stations (BSs) that are deployed far away from each other, it is general to assume them to be mutually independent. Nevertheless, after long-term evolution of cellular networks in various generations, this assumption no longer holds. Instead, the BSs, which seem to be gradually deployed by operators in a service-oriented manner, have embedded many fundamentally distinctive features in their locations, coverage and traffic loading. These features can be leveraged to analyze the intrinsic pattern in BSs and even human community. In this paper, according to large-scale measurement datasets, we build up a correlation model of BSs by utilizing one of the most important features, ie., spatial traffic. Coupling with the theory of complex networks, we make further analysis on the structure and characteristics of this traffic load correlation model. Numerical results show that the degree distribution follows scale-free property. Also the datasets unveil the characteristics of fractality and small-world. Furthermore, we apply collective influence (CI) algorithm to localize the influential base stations and demonstrate that some low-degree BSs may outrank BSs with larger degree.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
