Resource Management Of Heterogeneous Wireless Networks Based On Energy Efficiency

In recent years,with the rapid development of new generation information technologies such as mobile Internet and Internet of Things,the types of mobile communication services have continued to increase.In order to meet the requirements for system terminal capacity and transmission rate of massive terminal connections,Heterogeneous Network(HetNet)emerges at the historic moment,which provides users with a better service experience by deploying low power cell nodes on a large scale within the range of the macro cellular network.Since,the mobile network traffic has obvious spatial and temporal heterogeneity,various types of base stations are in a low load state for most of the time,which leads to serious energy consumption problems.In this context,the design of efficient resource management methods to reduce the energy consumption of base stations and improve the energy efficiency of entire network have become an important research topic for heterogeneous networks.Aiming at the energy efficiency problem in the two-layer heterogeneous network,the thesis takes base station sleeping and power control as the main technical schemes to carry out the energy efficiency-based resource management research.Firstly,this paper puts forward a small base station management algorithm based on user access after network adaptive clustering is completed,which uses the improved chaos quantum particle swarm optimization algorithm to determine the combination of base stations that enter the sleep mode,and then according to the network load situation,using the neighboring base station assisting method to wake up the dormant base station when necessary,which implementes the dynamic switching of the sleeping mode and the wake-up mode of the small base station.Then,the macro base station power control is combined with the small base station dormancy technology,based on the user subchannel allocation,a macro base station non-cooperative power control game algorithm is proposed.The algorithm utilizes the utility of game theory to model the energy efficiency optimization problem,and with the help of iterative algorithm to obtain the energy efficiency-optimized macro base station power strategy,which implementes the adaptive adjustment of the macro base station transmit power.Finally,the energy efficiency-based resource management scheme proposed in this paper is experimentally verified,and the simulation results show the effectiveness and feasibility of the proposed scheme.The scheme realized the optimization goal of improving the overall energy efficiency of the network on the basis of ensuring the quality of service(QoS),producing better energy saving effects.