System Utility Optimization Of Heterogeneous Cellular Networks Based On Software Defined Network In 5G

The fourth-generation(4G)mobile communication system has evolved rapidly in recent years,which has been successfully operated in many countries.In order to meet the explosive growth of mobile devices and data,the research and development in fifth generation(5G)mobile communication system and related technology have become the key point of the entire industry,especially,Software Defined Network(SDN)and Heterogeneous Cellular Networks(HCNs)promising research areas.In this paper,combining SDN and HCNs in the environment of 5G,we design a HCN model based on SDN,where the objective is to improve the whole system performance from multiple dimensions.Unlike most existing studies on the system optimization of wireless networks,a series of unrealistic hypothesizes and tractable methods have been used in this paper.Based on the Homogeneous Poisson Point Process(HPPP)and Cell Range Expansion(CRE),we derive the mathematical expressions of the maximum achievable data rate,the relative load ratio of BS,user's satisfaction,hand-off and so on.In addition,we introduce the utility theory to map the overall system performance and various factors into utility functions,and then directly analyze the utility function to manage the communication system.Due to the fading characteristics and randomness of wireless channels,the utility value of overall system obtained by the SDN controller is a random variable based on the feedback information.Therefore,we formulate the biasing selection problem in the model of wireless network as a discrete stochastic optimization problem to search the maximum utility value and corresponding to the optimum bias value.Besides,the convergence and complexity of the discrete stochastic optimization algorithm have been fully verified.Finally,a large number of simulations are performed for the theoretical derivation and algorithm of each module.The simulation results show that the system load balance can be well resolved through the CRE.What's more,the coverage probability and user satisfaction can also not be reduced to a great extent.Besides,the proposed discrete stochastic optimization algorithm can quickly converge to the best bias factor value.