Research On Resource Scheduling Algorithm Of NOMA System Under Fairness Constraints

Since the commercialization of the fifth-generation mobile technology,the number of communication devices in the network has been increasing,and future applications and scenarios are demanding higher requirements for information transmission,which poses great challenges to the design of mobile communications.Non-orthogonal multiple access(NOMA)technology can achieve higher throughput and support larger-scale device access compared with traditional orthogonal multiple access(OMA)technology.Therefore,NOMA is considered a key technology for future mobile communications.However,to maximize the throughput of the communication system,more power needs to be provided to the system and more resources need to be allocated to users with good channel conditions.Maximizing the throughput of the communication system under given power and fairness constraints can improve the user experience in the system and conform to the concept of green communication.User grouping and power allocation are key factors that determine the throughput and fairness of NOMA systems.This paper studies the resource allocation problem of NOMA systems under fairness constraints.Firstly,this paper uses an alternating iterative power allocation algorithm to improve system fairness and throughput with inter-group and intra-group fairness constraints.Secondly,this paper combines the user grouping scheme based on user channel gain with equal interval and unequal interval,which further improves fairness and throughput.Finally,this paper combines reconfigurable intelligent surface(RIS)technology to further improve the performance of the NOMA system.The main research work and achievements of this paper are as follows:(1)A user grouping algorithm based on the channel gain variation coefficient is proposed to ensure system fairness in dense user distribution scenarios.Simulation results demonstrate that the proposed algorithm improves the throughput gain of user groups with minimum channel gain difference and ensures overall system fairness.(2)A fairness metric based on rate variance is proposed,and an alternating iterative optimization algorithm for joint intra-group and inter-group power allocation is designed based on this metric.The power allocation algorithm maximizes system throughput under minimum fairness constraints within and between groups.Simulation results show that the proposed fairness metric has a fixed value range and better sensitivity,making it suitable for comparing fairness in systems with different numbers of users.The power allocation algorithm can simultaneously consider intra-group fairness,inter-group fairness,and system fairness.(3)For the resource scheduling problem in the reconfigurable intelligent surface assisted nonorthogonal multiple access(RIS-NOMA)system with sub-link structures,a joint iterative optimization algorithm is proposed,which includes relaxation variables,base station-side power allocation,and RIS-side precoding matrix.Simulation results show that the RIS-NOMA scheme with active sub-link structures based on the proposed algorithm has higher energy efficiency compared to RIS-NOMA with active full link structures,and it achieves higher spectrum efficiency and energy efficiency compared to traditional passive RIS-NOMA.