Software Defined Small Cell Networking under Dynamic Traffic Patterns

Software defined networking (SDN) has the potential to meet the requirements of the next generation traffic and service requirements. It is especially feasible and flexible when combining with small cell networks, which emerges into a software defined small cell networking (SDSCN) framework. SDSCN stands a chance to play a fundamental role in developing future 5G networks. It is particularly a challenging task to deploy dense small cell networks in the presence of dynamic traffic patterns and severe co-channel interference. Based on the SDSCN framework, in this paper, we propose a traffic clustering method to obtain all traffic patterns in a given area and an energy-efficient scheme to deploy and switch on/off small cell base stations (s-BSs) according to the prevailing traffic pattern. The simulation results indicate that our scheme can meet dynamic traffic demands with optimized deployment of small cells and enhance the energy efficiency of the system without compromising on the spectrum efficiency and quality-ofservice (QoS) requirements. In addition, our scheme can achieve very close performance compared with the leading optimization solver CPLEX and find solutions in much less computational times than CPLEX.