Research On Resource Management Strategy In C-RAN Systems

Recently,as the proliferation of smart mobile devices and over-the-top(OTT)applications has resulted in exponentially increasing data traffic demands,wireless networks have shifted from traditional connection-centric communications such as phone calls and messages to multimedia content-centric communications such as video and content sharing.Cloud radio access networks(C-RAN)is expected to be a transformative architecture in the 5G networks in order to adapt to this change in traffic demands,improve the resource utilization and reduce the network deployment costs.Compared with the traditional base station,a typical feature of C-RAN is that the architecture consists of a baseband processing unit(BBU)and some radio remote heads(RRHs).Due to the flexibility of C-RAN architecture,it has shown great potential for resource management and technology convergence.Under this background,the thesis aims to research on the resource allocation strategy in C-RAN for reducing the system power consumption through comprehensive utilization of wireless communication resources,computing resources and cache resources.The main contributions of this thesis are as follows:Firstly,this thesis investigates the research background,significance and current situations of C-RAN architecture.The importance of resource management in C-RAN has been expounded and some key technologies in C-RAN has been summarized.Then,a cross-layer resource allocation strategy in C-RAN is studied by considering the computing resources in BBU pool and the wireless communication resources in RRH with the user delay constraints.Using the queuing theory,the cloud processing process and transmission process are described as a two-line queuing model.The optimization problem is to dynamically adjust the mapping among virtual machines(VMs)which is software defined in the BBU pool,RRHs and users.Our goal is to minimize system power consumption while ensuring user latency.An improved genetic algorithm is used to solve this optimization problem.Finally,the proposed algorithm is compared with the DL algorithm to verify the effectiveness and feasibility of the algorithm through simulation.Finally,in order to reduce the cost of fronthaul and backhaul,this thesis introduced the caching mechanism in the C-RAN architecture.A cooperative hierarchical caching placement strategy which is composed of cloud cache and edge cache is proposed.The optimization model of minimizing system power consumption is established with the condition of RRH maximum transmit power limit and minimum user transmit rate limit.And the genetic algorithm is used to solve this optimization problem.Finally,the validity of the proposed caching strategies and algorithms is verified by simulation and the simulation results under different conditions are given.