Research On Resource Allocation Scheme In Cache-enabled Small Cell Networks

With the development of society,people’s requirements for mobile communication networks are getting higher and higher.Traditional macro cellular networks can no longer meet people’s requirements for high speed,low latency,and large capacity.Intensified network deployment has become a trend.Therefore,the small cell network with many advantages has attracted more and more attention.With the increase of network speed,Internet applications have also developed vigorously,such as online music,video,shopping,etc.More and more people use these rich Internet applications through mobile devices such as mobile phones and tablets.The network traffic has increased the burden on the network.In order to relieve the traffic pressure,the cache is introduced into the small cell network,and the content that the user needs can be obtained directly from the cache of the small base station,instead of requesting from the content provider on the Internet.The dense deployment of small cell networks and the introduction of caches have also brought new problems.In order to reduce interference and energy consumption in the network,and improve system throughput,an effective resource allocation method is required;in order to enable users to obtain content from the cache as much as possible To make full use of cache resources,an effective cache method is required.This paper studies the resource allocation scheme in a small cell network with cache enabled.The specific research content is as follows:(1)Establish a small cell system model with cache enabled,deduced the user’s transmission rate and the total transmission rate of the system with and without cache.The process of resource allocation is divided into two stages: cache placement and content transmission.(2)Cache placement phase: Many studies put cache placement from the perspective of content popularity,without considering the impact of content size on the placement plan.This paper comprehensively considers the two factors of local content popularity and content size,and establishes an optimization problem with the goal of maximizing local traffic load.The optimization problem can be further decomposed into multiple independent knapsack problems.For each knapsack problem,a dynamic programming algorithm is used to solve the maximum load of local traffic,and a backtracking algorithm is used to solve the corresponding buffer placement scheme.The simulation results show that the proposed cache placement scheme is better than the comparison scheme in cache hit rate and traffic offload rate.(3)Content transmission phase: This article uses an improved genetic algorithm to allocate wireless resources.In order to reduce the complexity of the problem,the weight of the user to each small cell is calculated based on the two factors of buffer and distance,and the user is associated to the small cell according to the weight and the sub-channels are allocated.Then,an improved genetic algorithm is used to allocate the power of the sub-channels.In order to make the genetic algorithm have better search ability and convergence,this paper improves the fitness function,crossover operator and mutation operator,and also adopts adaptive crossover probability and mutation probability.The simulation results show that the scheme proposed in this paper is superior to the comparison scheme in system throughput.