Base station and service social network and its application in cellular networks

Abstract

With the rapid development of wireless networks, the fourth-generation (4G) communication network is becoming increasingly popular and the fifth-generation (5G) network is expected to be commercialized by 2020. Many types of new services are being gradually applied mobile terminals with increasingly complex data in terms of diversity, scale, and dimension. It has become a popular research topic to optimize the base station deployment as well as resource scheduling strategy to meet various service requirements based on the cognizing of cellular network service pattern. We introduce a social network analysis method and propose a novel method to build service social network and base station social network (BSSN) for typical wireless network based on a study of wireless big data in practical networks. Additionally, traffic fluctuations can be predicted based on selected several typical very important base stations (VIBS), and caching strategies for cellular network can be optimized based on BSSN. This work provides insights and possible solutions for traffic monitoring, congestion prevention, network deployment and optimization, as well as resource scheduling optimization based on the characteristics of big data in cellular network.