Fast Time-Varying Channel Estimation For Massive MIMO Wireless Communication Systems On High Speed Rail

High-speed railways have increasingly become the first travelling choice for the Chinese people due to its convenience and flexibility.The construction of high-speed railway networks in China is also a top priority for national infrastructure construction.China is building an "eight vertical and eight horizontal" railway networks.Meanwhile,the fifth generation(5G)mobile communication technologies which aims at high data rate,short delay and low energy consumption,have gradually entered a new era of commercialization.Wireless communications on high-speed railways have the features of fixed tracks,continuous wide-area coverage,and high mobility.Therefore,5G technologies on high speed railways are important and challenging,which has received extensive attention from experts and scholars.Large-scale antenna array technology is one of the core technologies of 5G.It has been shown that the deployment of large-scale antenna arrays at base stations can significantly improve the network capacity and enhance user experience.5G requires 100 Mbit/s data rates per user on high-speed railways.To realize this goal with large-scale antenna array,a key challenge is fast time-varying channel estimation.Due to the high mobility,complex and changeable terrain,and large-scale antenna structure,the characteristics of the wireless channels in the high-speed railway are very different from those of the conventional wireless communication scenarios.The difficulty lies in how to design a channel estimator with low computational complexity,small pilot overhead and few pilot pollution according to the characteristics of large-scale antennas.Traditional channel estimation algorithms fail to address these problems,which is the focus of this paper.The main topic of this thesis is the fast time-varying channel estimation technology for wireless communication systems with large-scale antennas on high-speed railways.This paper proposes the uplink and downlink channel estimation solutions for high-speed rail scenario where the base station deploys large-scale antennas:(1)For the uplink,a system model based on orthogonal frequency division multiplexing(OFDM)is first designed according to the characteristics of the large-scale antenna high-speed rail scene.The characteristics include the requirement of serving multiple users,the base station equipped with antenna linear array,the time-varying channels and abundant surrounding scatterers.Using the sparse nature of the angular domain of the large-scale antenna array,a channel estimation algorithm is designed.Then,the estimation accuracy of the algorithm is improved by separating the parameters of each channel through angle rotation and pilot design.We also derive the Cramer-Rao Lower Bound(CRLB)of the estimator.Finally,the simulation results verify the effectiveness of the proposed algorithm.(2)For the downlink,we propose a channel estimation scheme with beamforming vectors.The design of this vector uses the angle domain information estimated by the uplink.After the system adopts this vector,the estimation value of the channels can be obtained through the Least Square(LS)algorithm.Then the theoretical lower bound of the scheme is derived.Finally,the simulation results verify the effectiveness of our proposed algorithm.