Research On Non-orthogonal Multiple Access For 5G

Non-Orthogonal Multiple Access(NOMA)has been widely accepted as a key candidate multiple access technology for 5G systems to address rapidly growing mobile data traffic and the demand for massive connectivity.NOMA demonstrates its superiority over Orthogonal Multiple Access(OMA)systems,both in terms of spectral efficiency and system throughput,as well as in user fairness,low latency and large-scale connectivity.In addition,it has good compatibility with the current communication architecture.This thesis mainly studies the application of NOMA technology in 5G scenarios and propose the novel algorithms of its key technologies.Main work and innovations are summarized as follows:This thesis firstly takes the downlink of two users as an example,expounds the basic principles of NOMA technology,and analyzes the performance gain brought by NOMA in terms of throughput and connection number compared with traditional OMA.Study the key technologies in the application of NOMA,and combine the three typical business scenarios of 5G to analyze the huge potential of NOMA in future application scenarios.Reasonable user pairing is beneficial to reduce the inter-group interference that cannot be eliminated by Zero-Forcing Beamforming(ZFBF)in MIMO-NOMA system and to ensure that NOMA users can successfully pass the Serial Interference Cancellation(SIC)to decode.In this thesis,a novel user pairing algorithm is proposed in MIMO-NOMA system.By applying the classic Hungarian algorithm,the NOMA user pairing problem is transformed into an assignment problem,and the benefit matrix is established through the user's channel characteristics to solve the optimal matching scheme under the constraint condition.The simulation shows that the proposed algorithm improves the system throughput by about 35%compared with the random sprinkling point in the downlink MIMO-NOMA scenario where the single cell has 2?128 users randomly scattered.Compared with the classic two-stage pairing algorithm,the improvement is about 5%,which verifies the effectiveness of the proposed scheme.In addition,this thesis studies the differences between traditional MIMO communication and millimeter-wave scenario,and establishes the system model of mmWave-NOMA,including user dropping based on Poisson cluster process(PCP)and the establishment of single-path millimeter-wave channel model.A machine learning based user clustering algorithm is proposed,which uses limited Channel State Information(CSI)to quickly divide users in a cell into clusters.By adopting Maximum Ratio Transmission(MRT)strategy,the complexity of beamforming design is reduced.The simulation shows that the system throughput of the simulated transmit power is 0?30 dBm,and the proposed scheme is about 30%higher than the random beamforming scheme of mmWave-NOMA,which verifies the performance of the proposed scheme.