Research On User Grouping And Power Allocation Scheme For Non-Orthogonal Multiple Access Systems

With the rapid development of mobile Internet and Internet of Things,the next generation mobile communication system(5G)needs to provide higher transmission rate,more spectral efficiency,more network access equipment and lower delay communication.Faced with the severe situation of the future,the communication industry has proposed a variety of new multiple access technologies,NOMA(Non-orthogonal Multiple Access)is one of key technologies.Because of the power domain multiplexing technology enables multiple users to share the same time and frequency domain resources,so that it is introduced in NOMA system on transmitter side.The traditional resource allocation scheme can't meet its needs.Therefore,this thesis focuses on the user grouping and power allocation scheme in NOMA system.Firstly,the basic principle and technical characteristics of NOMA are described.At the same time,several classical power allocation algorithms are introduced.Three kinds of signal detection techniques are introduced,including two kinds of successive interference cancellation algorithm and one kind of joint detection algorithm.This paper compares the advantages and disadvantages of existing several new multiple access technologies in 5G system.Thus,the foundation for the subsequent research work is laid.Then,based on maximum the capacity in downlink NOMA system,a user grouping and power allocation scheme is proposed both for the subcarrier and power optimization problem.The user grouping strategy is based on greedy algorithm that user selects the best option of the current step as the optimal strategy,and the complexity of the exhaustive algorithm in this scheme is reduced.Based on the result of this user grouping strategy,this algorithm combines the water-filling power allocation method with FTPA(Fractional Transmit Power Allocation)method,then obtains subcarrier power and power of multiplexed users,in order to optimize the system capacity.The simulation results show that the improved power allocation algorithm can effectively improve the capacity of NOMA system.Finally,a power allocation scheme based on improved particle swarm optimization(PSO)is proposed for the energy efficiency in downlink NOMA system.The scheme utilizes the characteristics of particle swarm optimization and fast convergence abilityby simulating the foraging process of birds.The particles in the particle group learn from the best position of itself and the best position of the population.The particles constantly adjust their movement speed and their own position.After several iterations,the optimal solution can be searched in the solution space to solve the problem.The algorithm solves the power allocation problem based on energy efficiency under the premise of user rate requirements.The simulation results show that the proposed scheme can effectively improve the energy efficiency of NOMA system.