Research On Integration Transmission Of Millimeter-Wave Massive MIMO-NOMA

The development of modern wireless communication has shortened the distance between people,and wireless communication is playing an increasingly important role.The future 6G will continue to develop towards higher speeds,lower latency,wider coverage,and stronger security and reliability.To meet the growing demand for larger connections and massive traffic in future wireless communication systems,research needs to be conducted in the area of higher frequency bands such as millimeter wave(mm Wave)communications,more antennas,and more advanced multiple access technologies.The combination of mm Wave massive Multiple-Input Multiple-Output(MIMO)systems and Non-Orthogonal Multiple Access(NOMA)technology can meet the aforementioned requirements.The traditional NOMA system is based on user-level Successive Interference Cancellation(SIC).Taking the uplink as an example,the receiver first demodulates and reconstructs the signal from the strong user,and then removes the signal from the strong user in the receive signal.In contrast,the proposed Group-level Successive Interference Cancellation(GSIC)is based on grouplevel processing.The principle of GSIC is to first divide users into groups and use Space Division Multiple Access(SDMA)for transmission within each group.At the receiver,the strong user group signals are demodulated and reconstructed first,followed by removing the strong user group signals from the received signal.Based on this,this thesis applies the GSIC technology to the mm Wave massive MIMO-NOMA system,and studies the maximization of energy efficiency and minimization of the total system power.The main research contents are as follows:First,a mm Wave massive MIMO-NOMA uplink model is introduced based on GSIC technology,which utilizes user channel gains to divide users into groups.Intra-group transmission adopts SDMA technology,while NOMA transmission is used between groups.Analog beamforming matrices and digital beamforming matrices are designed for each group.The analog beamforming matrix and digital beamforming matrix are designed for each group.As the objective is to maximize energy efficiency,it is difficult to solve the problem directly due to the concave objective function.Therefore,it is transformed into the form of the subtraction of two concave functions,and then converted into a convex optimization problem using an auxiliary function.Based on this,a two-stage power allocation algorithm is proposed to solve the power allocation problem.Simulation results show that the proposed solution can effectively improve system energy efficiency.Next,the power minimization problem of the uplink mm Wave massive MIMO-NOMA system is investigated and the performance of the hybrid beamforming under fully-connected and partiallyconnected structures is analyzed.Specifically,the users are divided into groups according to the different channel gains of each user,and then the analog beamforming matrix is designed for each group of users.Joint optimization of digital beamforming and power control is performed,and a parallel iterative algorithm is proposed to solve the optimization problem.The simulation results show the proposed framework outperforms the traditional scheme in terms of the total system power.