Traffic Characteristics Recognition And Service Mechanism In Next Generation Mobile Networks

Rapid growing demand for mobile data traffic spurs service innovations and creative applica-tion scenarios, which challenge capacities and service provision of the next-generation (5G) cellular networks. Many standard organizations and industrial companies begin to research the architecture and technologies of the next-generation (5G) cellular networks. Recently, engineers and researchers put a high value on the real measurement data to the modeling and designing work. In this disser-tation, we analyze a great many traffic data from real cellular networks to discover the patterns of network, subscribers and services. After that, based on the idea of software-defined network, the architecture of5G networks as well as network management method are proposed. Specifically, we investigate traffic patterns and service mechanism of the next-generation cellular networks, while the contents are listed as follows:Traffic patterns:we first model the spatial traffic density and discuss the traffic correlation in real cellular networks. The model could be applied to generate traffic distributions in different types of areas. Then the predictability of cellular traffic is investigated by information entropy theory. We find that a power-law distribution fits both inter-arrival time and dwell time of human mobility more precisely, and new models on the distributions of inter-departure time and the number of arrived subscribers are also proposed to characterize other mobility patterns. Furthermore, user behavior patterns and traffic characteristics of mobile instant messaging applications are described by a joint ON/OFF model, and we evaluate the performance of cellular network running the service in various scenarios.Service mechanism:we first introduce a new metric called the Quality of Experience (QoE) index for different services, and propose a wireless context-aware service control method to manage the distinctive QoE requirements of different services. Then, we abstract the management scheme, and propose three approaches to alleviate the influence caused by various traffic bursts:baseband resource pool on cloud platform as wireless infrastructure to enhance the capacity and flexibility of networks, cloud core networks to provide dynamic extension and service flow control abilities, and software-defined bearer networks to simplify service delivery instructed by core networks. These cloud based approaches not only avoid the potentially negative impact from bursts, but also provide a software-controlled end-to-end service management framework for future cellular networks.