Research On Signal Detection Algorithm In Uplink MIMO-NOMA System

Non-Orthogonal Muliple Access(NOMA)technology is one of the key technologies of the 5G physical layer.Combining with the Multiple Input Multiple Output(MIMO),the significantly improved the spectral efficiency of the system is achieved,it also brings certain challenges to uplink multi-user signal detection.For this issue,the thesis focuses on the research on the uplink signal detection of the MIMO-NOMA system.The main contents are summarized as follows.1.Introduction to MIMO-NOMA Model and Summary of Classic Signal Detection AlgorithmFirst,the MIMO-NOMA system model is introduced in detail.Secondly,three traditional detection algorithms,including Orthogonal Matching Pursuit(OMP)algorithm,Iterative Hard Thresholding(IHT)algorithm and regularized orthogonal matching(ROMP)algorithm,are descripted.Also their computational complexity is provided.Finally,the performance of various detection algorithms is simulated and compared.2.Iterative Signal Detection Algorithm for MIMO-NOMA System Based on Improved Gradient Projection MethodAiming at the sparse characteristics of active users in uplink MIMO-NOMA multi-user systems,an iterative signal detection algorithm based on Improved Gradient Projection(IGP)Method for MIMO-NOMA uplink systems is presented.The algorithm uses the convex optimization idea to gradually approximate the true value of the signal through iteration.The simulation results show that the proposed algorithm has obvious advantages in Bit Error Ratio(BER)performance under different system configuration conditions compared with the classical detection algorithm.Moreover,with the number of active users in the cell increasing,the computational complexity of other algorithms increases greatly,while that of the proposed algorithm increases less.Compared with the traditional Gradient Projection(GP)algorithm,the algorithm of the IGP-based algorithm has the faster convergence performance,also the BER performance of this algorithm is better for the same number of iterations comparied with other algorithms.3.Iterative Signal Detection Algorithm for MIMO-NOMA System Based on Error EstimationAiming to improve the accuracy of the signal detection obtained by the traditional tracking algorithm,an iterative signal detection algorithm based on Homotopy algorithm using the error estimation for MIMO-NOMA system is presented.In this algorithm,the active users and their signals in the system are firstly estimated by Compressive Sampling Matching Pursuit(CoSaMP).Then the error analysis is performed with the results,and the signal detection error is estimated.Finally,the system error estimate is superimposed on the previous estimate to obtain a more accurate one.The simulation results show that the proposed algorithm has a significant improvement on system BER performance compared with the classical detection algorithm based on Minimum Mean Square Error(MMSE),OMP and CoSaMP.As the number of active users in the cell increases,the system BER performance of the algorithm improves greatly.Moreover,the proposed algorithm can greatly improve the detection performance of the system with the slight increase of the computational complexity compared with the CoSaMP algorithm.