Research On Joint Allocation Of Computing And Radio Resource In C-RAN

With the rapid development of mobile Internet,the number of users and data traffic continues to grow.On the one hand,operators should solve the high cost of ultra-intensive deployment of base stations and,on the other hand,solve the problem that the scarcity of spectrum resources can not meet the needs of users.As a green low-carbon new wireless network architecture,Cloud Radio Access Network(C-RAN)can solve the above problem.C-RAN system centralizes resource processing by utilizing the BBU pool formed by the large-scale centralized Baseband Units(BBUs),and cooperates with the remote radio heads(RRHs).It can effectively improve network performance.Using efficient and flexible computing resources and radio resource management schemes can take advantage of C-RAN system which offers the potential to solve the technical bottlenecks faced by wireless networks.However,how to schedule these resources and deal with their relationship still need further study.This research focuses on the joint allocation of computing resources and radio resources.The corresponding schemes are proposed to optimize the system power consumption and throughput.The main contributions of the research are as follows:1)Joint allocation scheme of computing resources and radio resources under QoS constraints.In order to achieve the joint allocation of computing resources and radio resources,this paper first introduces the computing requirements model,then a new QoS constraints are introduced to ensure the adaptability of the allocation results to the instantaneous channel changes.The problem of minimizing the total system power consumption is divided into two steps:user-virtual machine mapping establishment and transmission power allocation,so as to reduce the computational complexity of the algorithm and ensure its timeliness.Simulation results show that the proposed scheme can save more system power than the other two benchmark schemes.2)Joint allocation scheme of computing resources and radio resources with RRH cooperation.Computing resources to a certain extent,restrain the scale of RRH cooperation.The use of cooperation transmission technology can bring users a higher transmission rate,but the processing load and huge power consumption is also an issue to consider.This study combines the allocation of computingsources with RRH cooperative transmission,and proposes to solve the allocation of computing resources by building the user-virtual machine matching rather than the traditional packing algorithm,which provides more rational management.The system throughput is optimized by these three steps:RRH cooperation cluster initialization,user-virtual machine mapping establishment,beamforming vector design.The simulation results show that the proposed scheme improves the system throughput and energy efficiency compared with the benchmarking schemes,and at the same time,it also ensures the system power consumption savings.