Research On Integrated Resource Allocation Based On Coalition Game In Dense Network

The dense network proposed by 5G is a key technology that meets the user's growing demand for services.However,with the increasing density of base stations,the problem of co-channel interference becomes the main factor that restricts the application of dense network technology.In the dense network mode,the base station has a clustering distribution feature.The traditional single station adjustment network optimization mode gradually becomes a network optimization mode based on the base station cluster.At present,the main way to improve system performance is to reduce interference through time slot resource scheduling,frequency resource scheduling and cell structure adjustment.In the dense network mode,the existing single-dimension optimization solution is difficult to solve the problem of co-channel interference.Therefore,other network optimization solutions need to be explored.At the same time,if the gain of the signal-to-interference-plus-noise ratio cannot compensate for the loss of bandwidth,it will reduce the throughput of the network,so it is also necessary to adopt an appropriate scheduling method to reduce the interference and increase the system throughput.For the problem of allocation of resources in dense access networks,this thesis proposes an interference reduction scheme for allocation of multi-dimensional resources in dense access networks.It reduces the interference of dense access networks through multiple ways,including time slot resource scheduling,frequency resource schedulingand cell structure adjustment.According to the characteristics of the co-channel interference in dense access network,a joint optimization scheme is proposed that aims at maximizing the system throughput,combining the resource allocation and cell combination of the micro-base station.This scheme uses the graph coloring algorithm to search for the optimal resource allocation,adopts the mathematical method of coalition game to determine the coalition formation of the micro-base station,and then improves the system performance through technologies such as cell combination or time slot resource scheduling.The simulation results of the proposed algorithm show that the algorithm can maximize the system throughput on the basis of guaranteeing the quality of users' service.In order to solve the problem of cost of fiber laying under dense networking,wireless backhaul technology has become a new research hotspot.In the existing research on the resource allocation of access and wireless backhaul network,the cell structure adjustment of the access network is ignored.Aiming at solving this problem,this thesis proposes a network optimization scheme based on genetic algorithm for resource allocation of base station clusters.Based on this,it makes use of the cell merging based on coalition game to further optimize the network performance of access network.Simulation results show that the proposed algorithm maximizes the throughput of dense access and wireless backhaul networks while satisfying the users' rate requirements.