Research On Technologies For Mitigating Pilot Contamination In Massive MIMO Systems

Currently,massive multiple input and multiple output(massive MIMO)technology is considered as one of the most promising transmission technologies in 5G.Massive MIMO configures large-scale antenna arrays(from tens to hundreds)on the base station side and serves multiple user terminals on the same time-frequency resource by using spatial division multiple access technology,which greatly improves spectrum efficiency.However,there are still some challenges to be solved in practical application.This thesis focuses on the pilot contamination problem of time division duplex massive MIMO,and details as follows.1.In the thesis,a scheme combining discrete Fourier transform(DFT)and least square(LS)(named as DFT-LS)is proposed to mitigate pilot contamination.By making use of the high spatial resolution of massive MIMO,the DFT-LS adopt LS channel estimation,and transfer the LS estimation results to the angle domain by using DFT.Then the guard band is set in the angle domain by considering the angle of arrival(AOA)information to protect the desired channel information and suppress the interference channel information.Finally the desired channel information will be recovered by inverse DFT.According to two considerations,i.e.,whether the AOA information of desired signal at the base station is accurate and whether the AOA information of interference signal can be obtained,there are three cases of guard band setting criteria are discussed in details.Theoretical and simulation analysis shows that the DFT-LS can relieve the performance deterioration caused by pilot contamination at any case.2.The allocation of pilot severely impacts the pilot contamination,so the reasonable usage of pilot resources can mitigate the pilot contamination of the system.Finding the pilot allocation method that maximizes the cell and capacity can be abstracted into a traveling salesman problem.Based on the solution of the traveling salesman problem,a pilot allocation scheme based on hysteretic noise chaotic neural network(HNCNN)is proposed for the first time.Hysteresis noise chaotic neural network is a famous optimization tool,and its optimization ability is related to the designed energy function.This scheme combines the characteristics of pilot resource usage and the calculation method of maximizing the total cell capacity to design a new energy function.The simulation results show that the proposed network can converge to a better pilot allocation mode after a certain number of iterations.Compared with the random pilot allocation,the pilot allocation method based on HNCNN can reduce the influence of pilot contamination and improve the system performance.