Network Cost Optimization Based On C-RAN

Mobile data have grown exponentially owing to the advances of wireless technologies and the proliferation of mobile devices.Cisco Systems predicts that the global mobile data traffic will increase sevenfold between 2016 and 2021.The explosive growth of mobile data traffic is a huge challenge to the mobile communication network architecture,and it is urgent to reform the traditional network architecture.By centralizing the processing unit,the Cloud Radio Access Network(C-RAN)greatly improves the efficiency of using wireless access network resources and reduces the deployment cost and operating cost of operators,which is the research direction of new network architecture.This paper studies the network cost optimization based on C-RAN.The main research work is as follows:Firstly,it summarizes the technical background of the topic,the status quo and significance at home and abroad,and expounds the architecture,advantages and challenges of C-RAN.Then,the problem of cost optimization after the introduction of cache technology in C-RAN is studied.Nowadays,the deployment of cache in the C-RAN architecture is a research hotspot.This paper first introduced the cache strategy based on the largest group in graph theory in C-RAN.At the same time,a system model combining the C-RAN architecture and cache was designed.And sleep mode.The network cost optimization problem studied includes joint optimization of transmission power consumption and backhaul cost.This problem is an optimization problem with a norm-based objective function and non-convex quadratic QoS constraints.To solve this problem,semi-definite definite relaxation(SDR)method and continuous convex approximation(SCA)method are used.Simulation results show that the introduction of cache technology can effectively reduce the network cost,the performance of the maximum group cache strategy is better,and the switching of the base station mode can also greatly reduce the network cost.Then study the cost optimization of BBU in C-RAN.Most of the existing C-RAN network cost optimization problems focus on the RRH side.This article studies the C-RAN network cost optimization in conjunction with the BBU.The network cost includes the power consumption of the RRH and the rental cost of the virtual BBU.The virtual BBU in the system model can be started and closed as needed,RRH can enter sleep mode to reduce power consumption,and at the same time model QoS requirements as the delay of two queues in series,including the BBU processing queue and RRH transmission queue.The currently widely used integer linear programming(ELP)model can solve this cost optimization problem.However,the ILP model leads to higher computational complexity.Therefore,this joint problem is further decomposed into two subproblems:the user association problem and the BBU-RRH mapping problem.A Lagrangian relaxation algorithm is designed for the user association problem,and the BBU-RRH mapping problem is converted into a packing problem.This problem is solved by the Best Fit Decreasing Algorithm(BFD)algorithm.The simulation results show that the operation result of the proposed algorithm LAGA-BFD is very close to the optimal solution and saves a lot of calculation time.Finally,this article summarizes the research work done and looks forward to the future research directions of C-RAN.