Research On Wireless Resource Matching Theory In 5G Dynamic Environment

In the future,5G will become broadband network of high capacity,high energy efficiency and high service quality.However,it will also put the existed network resources and technologies in poor hands.The rational allocation and utilization of wireless network resources in dynamic network environment have played important role in solving the above problems.Therefore,based on the analysis of multi-homing services and hot spot high-capacity scenario for 5G communication system,this paper adopts convex optimization and game theory to achieve resource matching in dynamic network environment which aims to saving power consumption.The main works of this paper are given as follows.I.A resource matching algorithm based on matching probability index is proposed.Firstly,according to the concept of resource matching and the dynamic characteristics of wireless channel,two kinds of matching probability indexes are defined innovatively and the most suitable index is selected to construct the resource matching model for maximizing energy efficiency of all terminals subjected and guarantee requirements.Secondly,Rayleigh fading channel models are introduced to accurately reflect the dynamics of the wireless channel,and the complete expression of the matching probability index is deduced to establish the resource matching model.II.A two-layer distributed resource matching model based on statistical guarantee requirement is proposed.Firstly,the energy efficiency resource matching problem for multi-homing services under dynamic wireless environment is considered while the bandwidth has been allocated completely,that is,all mobile terminals maximize the energy efficiency under the constraints of its statistical guarantee.Secondly,according to the solution of optimization model,a two-layer distributed solution algorithm is proposed,in which the original problem is decomposed into the inner minimization of power consumption and the outer maximization of matching probability.Aiming at the special case that the model may have no solution,an improved resource matching model by relaxing the statistical guarantee parameters is given.III.A two-layer resource matching model based on Stackelberg game theory is proposed.Firstly,the utility function is designed according to the characteristics of network heterogeneity and participants' need in different game layers.This paper makes use of distributed non-cooperative game theory innovatively to conduct games between the participants.Only by this way can this algorithm achieve the optimal power allocation between BSs(Base Stations)and users.Secondly,considering the influence of business rate change under the dynamic network environment,an algorithm of updating the pricing factor according to the prediction of the business rate is presented.