Research On Resource Allocation In Data And Energy Integrated Communication Networks Based On Base Station Cooperation

With the rapid development of communication technology,the demand of rate of communication network is higher and higher,and the problem of energy consumption is becoming more and more serious.Data and Energy Integrated communication Networks(DEINs)can simultaneously transmit information and energy for the terminal,which greatly improves the convenience of the terminal and makes makes devices without batteries possible in future.Base Stations(BSs)share information and collaborate with each other in the network.This enables better decisions to be made when allocating resources.Further improve network performance,but this also makes the strategy of resource allocation need to consider more factors,more complex.First of all,this dissertation introduces DEINs,and makes a research on the resource allocation in DEINs.The related research is divided into two categories according to whether the base stations cooperate with each other.Next,three kinds of base station cooperation models are introduced.In addition,the relationship between the total transmission power of all the base stations and the energy harvesting requirements and the SINR requirements in the three cooperative models is compared and analyzed by simulation.The advantages and disadvantages of the three modes of cooperation are analyzed.Then,we study the problem of resource allocation in the Fully-Duplex(FD)centralised cooperative DEINs.The system model takes both uplink and downlink users into account.Considering the need for joint resource allocation between uplink and downlink systems,both full-duplex technology and self-interference brought by full-duplex technology are considered in the system.Although self-interference makes the system model more complex,the system model is closer to the actual situation.The optimization goal of the problem is to minimize the total power consumption with both uplink-downlink quality of service constraints and Energy Harvesting(EH)constraints.Four algorithms with different computational complexity are proposed.In the first algorithm,an BCD-based algorithm for solving high non-convex problems is proposed.And although optimization variables are nonlinear coupled under constrained conditions,its KKT convergence is proved.In the second algorithm,a CCCP-based iterative algorithm with KKT convergence is proposed by proper transformation and operation.Each iteration can be carried out by solving a Second-Order Cone Programming(SOCP)problem.Then,two low-complexity heuristic algorithms are proposed.One is based on zero-forcing(ZF)beamforming algorithm,the other is a combination of ZF beamforming and MRT beamforming.Through simulation,the four algorithms mentioned above are compared and analyzed,and the validity of the above algorithms is verified.Finally,this dissertation is summarized and the works that can be carried out in the future are prospected.