A Joint Optimization Scheme of Resource Allocation in Downlink NOMA with Statistical Channel State Information

In a real communication scenario, it is very difficult to obtain the real-time Channel State Information(CSI) accurately, so the communication systems with statistical CSI have been researched. In order to maximize the throughput of the downlink Non-Orthogonal Multiple Access (NOMA) system with statistical CSI, the formula of system throughput is derived at first. Then, according to the combinatorial characteristics of the original optimization problem, it is divided into two subproblems, that is user grouping and power allocation. At last, a joint optimization scheme is proposed. Genetic algorithm is introduced to solve the subproblem of power allocation, and Hungarian algorithm is introduced to solve the subproblem of user grouping. By comparing the ergodic data rate of NOMA users with statistical CSI and perfect CSI, the effectiveness of the statistical CSI sorting is verified. Compared with the Orthogonal Multiple Access (OMA) scheme, the NOMA scheme with the fixed user grouping scheme and the random user grouping scheme, the proposed scheme can effectively improve the system throughput.