Resource Allocation For Downlink NOMA Wireless Network With Imperfect CSI

Recently,the emergency of novel techonologies,explosive growth of intelligent terminal devices and high quality of users' service requirements,leading to the limited spectrum resources come more and more scarce.Therefore,communication scholars mainly focus on the technologies which can improve spectral efficiency,such as non-orthogonal multiple access(NOMA).In NOMA communication system,the transmitters use power-domain multiplex technology to encode and transmit,the receivers take advantage of successive interference cancellation(SIC)technology to perform decoding.Because of efficiently improved spectral efficiency and the number of users accessing to the network,NOMA has become one of key technologies in the next generation communication system.Current studies mainly focus on resource allocation under the assumption of perfect channel state information(CSI).However,because of the difficulty of obtaining perfect CSI in practical communication system,we have to study the NOMA system model under imperfect channel state information(ICSI).This thesis mainly studied the resource allocation problem of NOMA cellular network under the ICSI.Aming at optimizing the energy efficiency of the downlink of the system,we regard user matching scheme and the power distribution factor as variables to model mathematical problems,and a heuristic algorithm solution is proposed.First,full search power algorithm(FSPA)is a traditional scheme for the power allocation among NOMA user groups in the same channel,but the computation complexity increases exponentially with the number of users gradually increases,therefore,a suboptimal iterative power allocation algorithm is proposed in this thesis,which can reduce the complexity while approaching the performance of the FSPA algorithm.Second,different user matching schemes will affect the optimal power allocation factor of NOMA user group,so does the system performance.The existing user matching scheme usually uses two-way user selection,which is a complex way without achieving the optimal performance,to solve this problem,this thesis calculates the energy efficiency matrix based on the suboptimal iterative power allocation algorithm,then converts the problem into an allocation problem,so that the hungarian algorithm can solve the problem.After the power allocation between NOMA users and user matching,this energy efficiency problem is proved to be a quasi-concave function,and a gradient assisted dichotomy can be used to find the optimal solution.The simulation results show that the heuristic algorithm proposed in this paper can effectively approach the optimal energy efficiency performance of the full-space search algorithm while ensuring the quality of users,and greatly reduce the computational complexity.