| With the development of 6G(the 6th Generation Mobile Communication System),in addition to human-to-human communication,communication connections between things are becoming increasingly common in the future.The number of users in the network will show explosive growth,leading to the challenge of massive user access in the future.Non Orthogonal Multiple Access(NOMA)technology can effectively improve spectrum efficiency because it supports the transmission of multiple users’ signals on the same time-frequency resources,which provides a new idea for solving the problem of massive user access in the future networks.However,its effect depends on a reasonable user pairing scheme.Therefore,how to design a NOMA user pairing scheme and how to effectively apply NOMA technology to the future network architecture are key issues.This thesis focuses on NOMA based high efficiency access technologies for massive users in these two aspects.The main research content and contributions are as follows:To solve the problem that users with similar channel gain are limited in forming NOMA user pairs,a massive user access pairing algorithm based on power boosting is proposed.It improves spectrum efficiency of the system.Firstly,based on the condition that the transmission rate of NOMA users should be greater than that of Orthogonal Multiple Access(OMA)transmission,the relationship between the minimum additional power and the channel gain ratio is derived.Secondly,by exchanging power for spectrum efficiency,additional power is added to users with limited pairing to facilitate user pairing.The simulation results show that compared with the traditional OMA and NOMA hybrid transmission scheme,our proposed scheme can obtain significant spectrum efficiency gain with a little power efficiency degradation.To solve the problem of ground base stations’limited service capacity in integrated terrestrial-satellite networks under the massive user scenario,a joint optimization algorithm of multi-user pairing and access based on Reinforcement learning is proposed.It improves the system capacity.Firstly,based on the power constraints of ground base stations and the satellite,a mathematical optimization problem is constructed with the goal of maximizing system capacity.Secondly,NOMA pairing is proposed as a prerequisite for user access to the network,and the Actor-Critic(AC)is used to provide a parameterized strategy for user service base station selection.Simulation results show that compared with the satellite user Selection algorithm,the proposed algorithm can achieve the goal of increasing system capacity in a limited training round.To solve the problem of frequent user collisions caused by the limited number of preambles during random access for a large number of users in Internet of Things scenarios,a low collision random access scheme based on user grouping and variable delay is proposed.It improves access success rate and reduces access delay.Firstly,utilizing the advantage of NOMA technology in reusing the same time-frequency resources,users are grouped based on different base station received powers.Secondly,setting a variable waiting delay for user devices that initiate multiple requests allows collision devices to initiate access requests again at different time slots.The simulation results show that when there are 300 user devices initiating random access requests and they are divided into 10 groups,the proposed scheme has a 32.6 times higher probability of successful access than the traditional scheme,and the average access delay of the devices is reduced by 75.6%. |
