Research On Millimeter-wave MIMO Channel Estimation And NOMA Transmission In Space Information Network

As the development trend of the future moibile networks is air-space-terrestrial integrated network,this paper focuses on the space information network(SIN)construcred by the integration of satellite networks and terrestrial networks.And we combine the millimeter-wave(mm Wave),the multiple-input and multiple-output(MIMO),non-orthogonal multiple access(NOMA),beamforming(BF)and other technologies to establish a satellite communication system model.Then we explore the mm Wave transmission characteristics and establish a channel model.First,design a fast mm Wave MIMO channel estimation algorithm based on the cha nnel model.Then,as considering the large-scale MIMO will bring high computational complexity,signal processing overhead and expensive radio frequency chain(RF chain)cost,the antenna selection algorithm is studied in the mm Wave MIMO-NOMA system.The specific content is as follows:In this paper,we focus on the mm Wave band MIMO down-link channel in SIN,then we establish a sparse geometric-based mm Wave MIMO channel model.By exploiting the sparsity inherent to the mm Wave band channel,we propose an efficient adaptive random-selected multi-beamforming(ARM)estimation scheme,which can simultaneously estimates the mm Wave MIMO channel state information(CSI)for multiple terminal users in angle domain.The ARM estimation scheme measures of the CSI between the high throughput satellite(HTS)and multiple UEs by utilizing a series of random combinations of transmitting beamforming vectors and receiving beamforming vectors,To further improve the performance of ARM estimation scheme two improved ARM estimation schemes are proposed for different satellite business needs.In response to the short packet data transmission and long-term data transmission,we propose the ARM forcing adaptation beam selection(ARM-FABS)scheme and the ARM partially estimated beam selection(ARM-PEBS)scheme based on the satellite assisting information.Simulation results show that the proposed ARM estimation schemes can adaptively reduce the required number of measurements as the signal-to-noise ratios(SNR)increases and achieve a better tracking performance over a wide range of SNRs.After the channel estimation this paper studies the MIMO-NOMA transmission mechanism and the antenna selection of the SIN.By analyzing the theoretical performance of the mm Wave MIMO-NOMA downlink system,the NOMA users are grouped according to the distance and path loss.Further,we formulate the join antenna selection problem for the mm Wave MIMO-NOMA system and find the system performance is respectively related to the instantaneous channel gain of the strong user and weak user in the two-user NOMA group.Based on this we propose two joint antenna selection algorithms,named the continuous maximum antenna selection(CM-AS)algorithm that achieves the maximum sum rate and the discrete maximum antenna selection(DM-AS)algorithm that compromoses the uers fairness.The simulation verified that the CM-AS algorithm can achieve the optimal performance of NOMA exhaustive search algorithm(ESA),and the computational complexity of the CM-AS algorithm is lower.And the DM-AS algorithm considers user fairness while ensuring system performance.