Research On Precoding And Channel Estimation Of Millimeter Wave Massive MIMO System

Massive MIMO system can provide the fifth generation(5G)cellular network with high spectrum efficiency,energy efficiency and high reliability performance requirements,and is the key technology of the fifth generation(5G)cellular network.Massive MIMO systems are based on space division multiplexing technology,equipped with hundreds or thousands of antennas at the base station to increase channel gain.Due to the mutual interference between different antennas,this makes information processing more complicated.Traditional precoding techniques and channel estimation algorithms are no longer suitable for large-scale MIMO systems,and it is urgent to innovate and design better performance and lower complexity pre-processing.Coding scheme and channel estimation technology.In response to the two problems mentioned above,this article has conducted the following research:(1)In a large-scale multi-user multiple-input multiple-output(MU-MIMO)base station(BS),the power consumption of the digital-to-analog converter(DAC)accounts for a large portion of the total power consumption.Using a 1-bit DAC can greatly reduce the power Consume.However,using a 1-bit DAC for precoding in a large-scale MU-MIMO system will cause additional distortion and reduce system performance.Therefore,a nonlinear precoding algorithm based on Alternating Direction Multipliers(ADMM)is proposed.The algorithm transforms the constrained quantization precoding problem into an unconstrained form for solving,and simplifies the algorithm loop structure.Simulation experiment results show that the ADMM quantization precoding algorithm has the advantages of good system performance and low computational complexity.(2)The analog/digital hybrid precoder used in the current millimeter wave MIMO system will lead to the increase of spectrum efficiency loss and the high computational complexity of the algorithm.An alternate minimization hybrid precoding algorithm based on Riemann's steepest descent method(RSD)is proposed.By adopting a single loop structure that alternately optimizes the digital precoder and analog precoder,the complex nested loop structure in the traditional algorithm is simplified,and the gradient calculation method is improved,reducing the calculation complexity caused by the large matrix kronecker product;In order to further verify the performance of the algorithm,the proposed algorithm is extended to a broadband millimeter-wave MIMO system.The simulation results show that theRSD-Altmin method proposed in this paper can reduce the computational complexity of the hybrid precoding algorithm to have a faster processing speed,and at the same time it is closer to the optimal digital precoding spectral efficiency.(3)In millimeter wave(mmWave)large-scale multiple-input multiple-output(MIMO)systems,reliable estimation of wireless propagation channels is a key technology to achieve system performance.However,due to the high variability of the millimeter wave channel,the system cannot obtain reliable channel state information within a short pilot training time.Therefore,a millimeter-wave massive MIMO channel estimation algorithm based on Alternating Direction Multipliers(ADMM)is proposed.This algorithm uses the sparse characteristics of millimeter-wave channels and the low-rank characteristics of millimeterwave channel matrices to achieve Under the pilot training length,reliable channel state information is obtained.Simulation results show that this algorithm has lower channel estimation error and higher robustness than traditional channel estimation algorithms.