Research On The Planning Of Base Stations And The Strategies Of Service Caching For 5G Cellular Networks

At present,the infrastructure in the current network system is difficult to meet the needs of high transmission data rate and low latency requirement of task offload under 5G networks.Therefore,according to the characteristics of high transmission and low latency of 5G networks,deploying a large number of micro base stations with transmission and computing capabilities has become an effective solution.As we all know,the deployment of a large number of micro base stations can meet the increasing needs of users,but due to the difference in time and space of user requests,it is bound to cause some micro base stations to cause energy waste in certain periods due to excessive service.In response to this problem,micro base station activation proved to be an effective solution.At the same time,due to the limitations of the capabilities of micro base stations deployed in 5G edge networks(for example:limited storage resources can only cache some services,etc.),when some micro base stations with excessive resources are closed due to energy consumption problems,it will cause Edge networks cannot simultaneously meet the increasing diversity needs of users(for example:facial recognition,interactive games,etc.).In response to this problem,joint optimization of micro base station activation strategy and service cache strategy has proved to be an effective solution.This thesis studies base station planning and service buffering strategies under 5G networks from the following two perspectives.(1)In the thesis,the optimal deployment of micro base stations in the network planning stage is studied,and the optimal deployment strategy based on the spatial branch and bound algorithm is proposed.Combined with the characteristics of using millimeter wave communication under 5G networks,by minimizing the number of micro base stations deployed and optimizing their placement,minimizing the energy consumption of micro base stations and minimizing the execution delay of tasks.First,model it as a two-layer optimization problem.The upper and lower problems are all integer linear programming problems.Secondly,the upper and lower level problems are converted into equivalent continuous linear programming problems,which reduces the complexity of the problem.Then,using the KKT conditional replacement method,the two-layer optimization problem is transformed into a single-layer optimization problem.Finally,the problem is solved by the spatial branch and bound algorithm to obtain the global optimal solution.(2)The thesis proposes the Benders-1 decomposition algorithm for the joint optimization of micro base station activation and service cache that occurs during the network operation phase.While considering the energy consumption problem caused by the large deployment of micro base stations under the 5G network,it also takes into account the service caching problem caused by the limitations of the micro base stations' own capabilities.In this paper,combined with the interaction between service caching and base station activation,a new service caching strategy is designed to maximize the overall benefit of the edge network and model it as a mixed integer programming problem.Because the joint caching and activation problem is NP-hard,the problem is solved by the proposed Benders-1 decomposition algorithm into two sub-problems of base station activation and service caching,so that it can obtain a global optimal solution.(3)In the thesis,the optimal deployment strategy of the micro base station based on the spatial branch and bound algorithm and the Benders-1 decomposition algorithm proposed for the joint optimization problem of base station activation and service cache are experimentally verified and analyzed.Through the experimental results of the optimal deployment model of micro base stations,it is not difficult to find that the proposed micro base station deployment strategy combined with millimeter wave communication features can greatly improve the energy efficiency of micro base stations.The experimental results corresponding to the joint optimization of base station activation and service caching show that dynamic service caching can be utilized.By turning off idle micro base stations,while ensuring user service quality,the energy consumption of micro base stations is reduced and the overall benefit of the edge network is maximized.This paper also validates the Benders-1 decomposition algorithm,and the results show that it can obtain the optimal solution.