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

Abstract

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.INDEX TERMS Non-orthogonal multiple access (NOMA), spectrum resource and power allocation, global optimal search (GOS), adaptive proportional fair (APF) user pairing, fairness.

Non-Cooperative Game-Based Power Allocation for Energy-Efficient NOMA Heterogeneous Network

“…In [15], the problem of maximizing EE of NOMA system is solved by combining subchannel matching and power allocation with non-cooperative super-modular game model. In [16], the problem of spectrum resource and power allocation are converted into user pairing, subchannel matching and power allocation. In addition, proposed adaptive proportional fair algorithm (APFA) improves system throughput and user fairness compared with the traditional subchannel matching based on matching theory and power allocation with water-filling (WF) algorithm.…”

Power allocation with fairness for non‐orthogonal multiple access systems

“…Optimisation problems for single and multi‐carrier NOMA are formulated and an iterative solution is proposed. A similar problem for maximising the total system rate is formulated in [17]. The available power levels are discretised and pairs and optimal power levels are found by group search.…”

A Survey on Application of Non-Orthogonal Multiple Access to Different Wireless Networks

“…The impact of user grouping on NOMA performance is investigated in [11,56,[71][72][73][74][75][76][77][78][79][80][81][82][83]. The authors in [56] grouped users together whose channel gains differ significantly.…”

“…Considering the two user NOMA system, the authors derived a closed-form optimal solution with PF objective in order to obtain user pairing and power allocation. Based on adaptive PF technique, the authors in [79] proposed an algorithm in order to obtain optimal user pairing, spectrum resource, and power allocation. The results show that the proposed algorithm achieves a comparable throughput performance to the global optimal search method and water-filling power allocation schemes, while also enhancing fairness among users.…”