Research On Joint Optimization For Renewable Energy Cooperation And Resource Allocation In Cloud Radio Access Networks

In recent years,because of the huge number of wireless terminals and the deployment of radio acccess networks for serving them,cellular networks will suffer from an enormous growth of traffic load and network energy consumption that will lead to negative economical and environmental impacts,in order to solve these problems,cloud radio access network(C-RAN)has been proposed.The C-RAN architecture can realize the centralization of resource processing,and it is able to efficiently utilize resources according to the load to save energy.However,conventional wireless communication resource allocation schemes will face new challenges in this new radio access network architecture.At the same time,with the development of energy harvesting(EH)technology,it is possible that the base station can be supplied by green renewable energy.However,there is a mismatch between the distribution of renewable energy and user services in time and space,which results in low utilization of renewable energy.Under such backgrouds,the research on joint optimization for renewable energy cooperation and resource allocation in C-RANs with hybrid energy sources shows a great significance.In this dissertation,we focus on research on joint renewable energy cooperation and resource allocation in downlink transmissions based on C-RAN architecture.The goal is to maximize the sum rate of the overall network while satisfying the total energy cost constraint,considering different wireless communication resources optimization.The contributions are as follows.First of all,we study the problem of joint optimization for renewable energy cooperation and subcarrier allocation in downlink transmissions based on C-RAN architecture.The C-RAN is based on Orthogonal Frequency Division Multiple Access(OFDMA)system.Firstly,according to the characteristics of the downlink transmissions in C-RAN and renewable energy harvesting,we establish the system model of C-RAN powered by hybrid energy sources.Then,based on the system model,we formulate an optimization problem to maximize the sum rate of the overall network while satisfying the total energy cost constraint.For the reason that the optimization problem is Mixed Integer Non Linear Programming(MINLP),it is difficult to obtain the optimal solution.Thus,an improved hybrid-fitness function evolutionary(HFFE)algorithm is developed to derive a sub-optimal solution.Simulation results show that the proposed algorithm is effective and outperforms the mixed integer-laplace crossover periaux mutation(MI-LXPM)algorithm,morever,the technique of joint optimization for renewable energy cooperation and subcarrier allocation can significantly improve the network throughput,as compared to the conventional resource allocation technique without energy cooperation.The proposed technique can utilize system resources effectively.Then,we study the problem of joint optimization for renewable energy cooperation and resource allocation in downlink transmissions based on C-RAN architecture.The above joint optimization includes renewable energy cooperation,variable bandwidth sub-carrier allocation and power control.The C-RAN is based on Variable Sub-carrier Bandwidth OFDMA(VSB-OFDMA)system.Firstly,according to the characteristics of VSB-OFDMA,we establish a new system model of renewable energy cooperation and resource allocation.Then,based on the new system model,we formulate an optimization problem to maximize the sum rate of the overall network.The optimization problem is also a MINLP problem,which is solved by improved HFFE algorithm.Simulation results show that the new joint optimization technique can further enhance the network throughput,as compared to the joint optimization for renewable energy cooperation and sub-carrier allocation technique,and can obtain the network throughput gain which can not be reached by other joint optimization techniques.