Pilot Allocation And Channel Research For Massive MIMO Systems

With the rapid development of information and communication technology in recent years,smart living facilities have emerged in large numbers,and users have increasingly higher requirements for data transmission bandwidth,stability,and delay of wireless communication systems.Traditional Multi-input Multi-output(Multi-input Multi-output,MIMO)antenna technology has been unable to meet the rapidly growing demand for mobile data traffic.Massive MIMO technology,as the core technology for fifth-generation(5G)cellular network communication,has received high attention in the field of wireless communication research.Studies have shown that with multi-antenna technology,the system network capacity and the transmit efficiency of the transmitter will be increased by orders of magnitude,resulting in significant improvements in the performance of wireless communication systems.Massive MIMO technology is implemented by providing more active antenna arrays in base stations(BS),which can greatly increase data transmission rate and system capacity compared with traditional MIMO.The shows that pilot allocation strategies and better channel estimation algorithms for large-scale MIMO systems are the keys to improving system performance.This paper conducts research on system pilot pollution and data transmission channel characteristics.The work is arranged as follows:This paper analyzes the massive MIMO system model,and briefly explains the data interaction process between the user and the base station,and the characteristics of the wireless channel.First of all,for a better understanding of system pilot allocation and sparse channel estimation,Chapter 2 analyzes and summarizes the causes and effects of pilot pollution in a cell.In view of the problems in the current system,it briefly introduces several types of classic pilot allocation.Scheme and channel estimation algorithm,and analyze its characteristics.Secondly,the time division duplex(TDD)mode wireless channel characteristics are described,and the cell model is modeled according to the actual scene user location distribution characteristics.For some cell users,the pilot traffic is seriously polluted and the communication quality is extremely poor.The third chapter proposes a pilot allocation scheme that distinguishes users.The main idea of the algorithm is to classify the cell users according to the channel error factor value.After classifying,the user adopts the corresponding exhaustive method and the Hungarian algorithm for pilot allocation,and formulates the pilot allocation problem of maximizing the system downlink and rate.The iteration optimizes the current allocation scheme of the system to achieve the optimal pilot allocation.The simulation results show that the proposed pilot scheme can greatly improve the system performance with lower complexity.Finally,combined with massive MIMO technology to illustrate the channel characteristics of the system using millimeter wave communication,the signal transmission of millimeter wave system tends to present the multipath sparse structure of the system,and becomes obvious as the signal space dimension becomes larger.In the fourth chapter A sparse channel estimation algorithm based on the improved generalized Akaike Information Criterion(GAIC)is proposed.According to the large amplitude of the pulse amplitude at the effective tap,the algorithm uses the cost function to obtain the effective tap position and accurately perform channel estimation.The noise interference is reduced to a certain extent.The simulation results show that the proposed channel estimation algorithm has good noise suppression and multipath interference resistance.