Spectrum Resource and Power Allocation With Adaptive Proportional Fair User Pairing for NOMA Systems

In this paper, we investigate the spectrum resource and power allocation problem for the tradeoff between maximizing the sum rate and minimum rate requirements of users in non-orthogonal multiple access (NOMA) system. First, we formulate the NOMA techniques, basic principles, and double-objective optimization (DOO) problem. Then, the non-convexity of the DOO problem is converted into a single-objective optimization (SOO) problem by power discretization method. Global optimal search (GOS) algorithm is applied to solve the user-subchannel matching and power allocation problem. Due to its high complexity and unfairness among users, it is only suitable for determining the upper bound of users throughput performance. Finally, yet importantly, a spectrum resource and power allocation algorithm with adaptive proportional fair (APF) user pairing is proposed to convert the original optimization problem into user pairing, sub-channel, and power allocation. The users paired on the sub-channel are determined by the scheduling priority which is based on the equivalent channel gain. The BS dynamically adjusts the forgetting factor in the APF algorithm based on the variance of all the users' scheduling priorities so as to influence the update of users' scheduling weights. The power allocation stage proposes three power allocation schemes to ensure the users' minimum data rate requirements under the condition that effectively guarantees the correct execution of successive interference cancellation (SIC). The simulation results demonstrate that it can not only approach the throughput performance compared with the global optimal search and the classical water-filling (WF) power allocation using matching theory but also can improve the fairness of the users.