Channel Estimation And Precoder Design For Mm Wave MIMO Systems

In the context of increasingly scarce spectrum resources,millimeter-wave(mm Wave)communications has become a basic approach to satisfy the demand for large-bandwidth communication of 5G and beyond.And it is also a hot topic in the current academic and industrial circles.Due to the short wavelength,mm Waves are often combined with large-scale antenna arrays.This paper investigates problems involving channel estimation,hybrid beamforming(HBF)and large intelligent surface(LIS)aided communication,focusing on challenges of high implementation complexity and small coverage faced by mm Wave multi-antenna systems.The first part of the theis studies the channel estimation algorithms in the 5G NR downlink physical layer.5G adopts mm Wave communications and large-scale antenna arrays extensively to meet its high date rate demand,while channel state information(CSI)is indispensable for such technologies.This paper proposes channel estimation algorithms based on the tracking reference signals(TRS)to estimate the large scale properties including carrier frequency offset and timing offset.Before channel estimation,TRS are denoised by getting through a transform-domain window.After that carrier frequency offset and timing offset are estimated based on the correlation of TRS in the time and frequency domian,respectively.Numerical results have verified the effectivess of the estimation algorithms.The second part deals with the precoder design of a multiple-input sigle-output(MISO)multicasting system with a hybrid beamforming architecture.In a mm Wave communication system implemented with large-scale antenna arrays,conventional fully-digital beamforming requires one distinct radio-frequency(RF)chain per antenna and it quickly becomes unaffordable due to the high cost and excessive power consumption of too many RF chains.In response to this problem,the paper adopts a hybrid beamforming architecture which can significantly reduce the number of RF chains and proposes corresponding HBF algorithms.The main objective is to maximize the minimum received signal-to-noise ratio(SNR)of all users.To address the non-convex nature of the optimization problem,different techniques including semi-definite relaxation(SDR)and successive linear approximation(SLA)are employed and several heuristic algorithms are proposed.Numerical results show that the proposed algorithms are effective when compared with existing algorithms.The final part investigates the precoder design and performance of the new emerging LISassisted systems.Due to severe penetration loss and weak diffraction ability,mm Wave communications are sensitive to blockage by obstacles.LIS can introduce supplementary paths when the line-of-sight(Lo S)path of the millimeter wave signal is blocked.First we consider a single-input single-output(SISO)downlink system assisted by a LIS.The optimal phase shift design of the LIS is proposed exploiting channel state information(CSI)and the approximations of ergodic capacity as well as outage probability are derived.Then a LIS-assisted MISO downlink system is considerd.Based on the statistical CSI,favorable algorithms are proposed to address the joint design of the precoder and the LIS.Simulation results show that the proposed algorithms are quite effective and the theoretical approximaitons of ergodic capacity and outage probability are accurate.