Research On Hybrid Precoder With Low Resolution Phase Shifter In Millimeter Wave MIMO System

With the rapid development of wireless communication technology,mobile data traffic is increasing at an alarming rate.This large amount of mobile traffic has greatly exacerbated the spectrum congestion in the current frequency band,thus inspiring a strong interest in using the new spectrum for wireless communication.In wireless communication,millimeter wave works in the 30 GHz to 300 GHz frequency band,and the technical solution resulting from the combination of millimeter wave and hybrid precoding technology in large-scale multiple input multiple output systems is regarded as one of the key technologies of the new generation mobile communication system.Because it has rich spectrum resources,and can improve the system spectrum efficiency and energy efficiency.This paper will study the improvement of system spectral efficiency based on the reduction of power consumption in a millimeter wave large-scale multi-input multi-output system based on a low-resolution phase shifter.The main research results are as follows:1.In the millimeter wave large-scale multi-input multi-output system,the analog precoding algorithm with low-resolution phase shifter has a high algorithm complexity.To cope with the computational complexity problem,an improved iterative phase hybrid precoding algorithm is proposed.It decomposes the analog precoding optimization matrix into column vectors one by one,and uses the second-order rank matrix to obtain the suboptimal optimization function approximately.Then,the optimization function is transformed into a summation form and the optimal phase is obtained by iterative convergence.At the same time,in order to maximize hardware efficiency,an analog beamforming scheme with 1 bit resolution phaser is designed.Theoretical analysis and simulation results show that the proposed algorithm has lower computational complexity and better spectral efficiency.2.In the millimeter wave large-scale multi-input multi-output system,the analog precoding based on the low-precision uniform quantization phase shifter has high complexity,and the energy efficiency is not fully utilized.In order to effectively solve this problem,a hybrid precoding design based on convolutional neural network under non-uniform quantization is proposed.First,by using the weight coefficients of different beams in the channel transmission matrix,the original channel is reconstructed into a millimeter wave channel model in the form of lobes,and the quantization bits of the phase shifter are allocated according to the weight coefficients of each lobe,and then a non-uniform quantization simulation is constructed precode codebooks and reduce power consumption.Then,the analog precoding is used as the label of the corresponding channel transmission coefficient to construct the training data set of the neural network,and the analog precoding is predicted based on the training data set,so as to reduce the computational complexity.A large number of simulation evaluations show that the proposed algorithm has lower power consumption and its spectral efficiency is better than traditional algorithms.