Research On Non-Othogonal Multiple Access Power Allocation Algorithms In MIMO Systems

With the development of mobile communication technology,it has expanded from voice services to mobile Internet services.Due to the rapid development of the Internet of Things,mobile traffic has grown exponentially.However,the spectrum efficiency of traditional orthogonal multiple access and the number of users allowed to access are limited,which cannot meet the explosive user growth.Compared with the traditional orthogonal multiple access method,the non-orthogonal multiple access technology greatly improves the spectral efficiency of the system and number of users allowed to access.Combining non-orthogonal multiple access(NOMA)with multiple-input multiple-output(MIMO)technology can increase the throughput of the system without increasing the system bandwidth and the transmitting power of base station,and achieve the massive access requirements of 5G.For the MIMO-NOMA downlink system based on imperfect serial interference cancellation,this thesis studies the power allocation problem in MIMO-NOMA systems with throughput and energy efficiency as the optimization goals.Aiming at maximizing throughput in MIMO-NOMA system,a power allocation algorithm based on serial interference cancellation residual is proposed.First,we establish a Stackelberg game model,where the base station is set as a seller and users in the cell are set as buyers.Secondly,the Lagrange function is used to find the optimal power purchased by the user under the constraints,and this power is a function of the price.Finally,the optimal price set by the base station for each user is solved.During the game between the base station and the user,the base station dynamically adjusts the price to maximize its own revenue.Simulation results show that the throughput performance of the proposed algorithm is better than that of fractional order power allocation algorithm,and at the expense of a small amount of throughput,the computational complexity and the power consumption of the base station are both reduced.Aiming at the fact that the throughput and energy efficiency are not uniformly increasing and decreasing in most cases and cannot be optimized at the same time,considering serial interference elimination residue an energy efficiency power allocation algorithm based on Dinkelbach algorithm is proposed.Firstly,the base station and the user are constructed as a Starkberg game model,and the base station is set as the seller and the users are set as the buyers.Then the non-convex benefit function of the user is transformed into a convex problem through the fractional programming method.The Dinkelbach algorithm is used to iteratively solve the optimal energy efficiency.Simulation results show that the proposed algorithm has a better energy efficiency performance than the fractional power allocation algorithm.In addition,compared with the algorithm based on differential convex programming,the proposed power allcation algorithm in this thesis has a similar energy efficiency performance but lower complexity.