Research On Communication And Computing Resource Allocation Strategy In The C-RAN Combined With MEC

Cloud radio access network(C-RAN)architecture combined with mobile edge computing(MEC)can provide network access services and localized computing services with rich bandwidth,high reliability and low delay for user terminals,and effectively expand the computing capacity of user terminals.Therefore,it is one of the key research objects of bandwidth access technology.However,as diversified mobile services emerge in an endless stream,traditional resource allocation methods cannot meet the increasing user access requests,leading to problems such as low resource utilization rate,high energy consumption,long delay and deterioration of user quality of service(QoS)in the edge enhanced C-RAN.Therefore,based on the advantages and characteristics of MEC and C-RAN,this thesis proposes an energy consumption aware communication and computing resource allocation mechanism and an edge enhanced C-RAN resource allocation mechanism for balancing delay and energy consumption,in order to make full use of network resources,reduce network energy consumption waste,reduce network access delay,and ensure user QoS.In general,remote radio units(RRU)improve network access capability through intensive deployment,but this will lead to increased co-frequency interference and increased network energy consumption.Therefore,this thesis designs a user association strategy based on energy consumption perception to ensure user QoS firstly.And then,in order to make full use of MEC resources,reduce waste of energy consumption,this thesis design a heuristic algorithm based on collaborative computing offloading,priority in the task of the algorithm is offloaded to the macro base station(MBS)of MEC server,to alleviate the fronthaul link traffic load pressure,and according to the actual user demand distribution MEC resources,in order to improve the resource utilization of MEC server.The results show that the proposed algorithm can effectively improve the network throughput and reduce the blocking probability and network energy consumption.In edge enhanced C-RAN,reducing network access delay can improve user QoS.Reducing the number of active MEC servers can save service providers cost.Therefore,a load transfer algorithm with a two-level threshold constraint and a heuristic algorithm based on minimizing the number of active MEC are designed in this thesis.First according to determine a user level one constraint set association,and then according to level two constraint set determine the baseband signal processing server position,in this way to ensure users QoS,then according to the baseband signal processing information processing server resources,determine appropriate MEC server,in the protection of MEC of resource utilization at the same time,in order to realize the goals to reduce energy consumption.The results show that the proposed algorithm can effectively reduce the network delay and energy consumption.Finally,the research work of this thesis is summarized,and the future research direction is prospected.