Research On User Attachment And Cell Switching Strategy For Network Energy Efficiency Optimization

With the rapid development of communication technology in recent years,mobile data traffic presents an exponential explosive growth trend.In order to meet the needs of users for data rate,operators have to build more and smaller base station,so ultra-dense network architecture has become a widely accepted network architecture trends.In indoor and outdoor hot spots,ultra-dense network architecture densely deploys small base station with low power,enhancing spatial multiplexing degree by the deployment of encrypted cell.This architecture is an effective method to solve the problem of data traffic explosive growth.However,in this network architecture,the intensive deployment of base stations brings a large amount of energy consumption,which affects the energy efficiency of the network.This paper discusses two scenarios of static and dynamic mobility,and proposes corresponding improved user attachment and cell switching strategies respectively as follows:For static scenarios,this thesis proposes an energy efficiency optimization scheme based on separation of control plane and user plane.In the ultra-dense network deployment scenarios,the traffic data would change with time and space.Sometimes,many base stations are at a low load level,causing a large amount of energy consumption and affecting the network energy efficiency.In this paper,the multi objective knapsack model is constructed with the goal of network energy efficiency,and the unnecessary base station is switching off into hibernation mode by greedy algorithm,thus reducing energy consumption and improving network energy efficiency.Meanwhile,in order to ensure the coverage of base station in the process of switching off the base station,we user Tyson polygon theory to adjust the base station transmitting power.Simulation results show that the proposed strategy can effectively switch off unnecessary base stations and greatly improve the network energy efficiency.For dynamic mobility scenarios,an energy efficiency optimization strategy based on continuous time between mobile users and base stations is proposed in this paper.Most of the previous work on the proposed base station energy efficiency scheme is based on static instantaneous information.However,for high mobility scenarios,this.scheme will lead to frequent base station switches.Taking the blocking probability,the equipment life and the energy consumption in the process of base station switching,the scheme is difficult to be applied in practice.Therefore,this paper proposes a more practical energy efficiency optimization strategy based on the mobility in a continuous period of time.Firstly,the Markov model is established for the energy efficiency optimization problem.Then,for each Markov state point,the user's decision factor is normalized,and the weight is calculated based on the fuzzy matrix.We build the utility function based on the weight and obtain the optimal solution.Finally,according to the calculated Markov state point,the problem is transformed into the shortest path problem and solved.The simulation results show that the proposed algorithm can optimize the network energy efficiency more effectively when considering the actual constraints.