Research On Channel Estimation In Massive MIMO Systems

As society continues to evolve,the future will require larger capacity,higher speed,and more reliable mobile communication networks to meet the growing needs of people.5G technology has obvious advantages over 4G in terms of energy efficiency,transmission rate,spectrum utilization and coverage,and will be widely used in the coming years.As one of the key technologies in 5 G,Massive MIMO technology is widely concerned by domestic and foreign scholars.It is an extension of MIMO technology.By increasing the number of antennas at the base station,channels of different users are close to orthogonality so as to better reach the limit of channel capacity.In the traditional channel estimation method,multiplexing the same pilot sequence in different cells may lead to mutual interference of channel estimation values of users using the same pilot in neighboring cells,that is,phenomenon of pilot pollution,presence of pilot contamination.It will limit the improvement of the performance of Massive MIMO systems.In order to solve the problem of pilot contamination,this paper proposes two novel channel estimation schemes based on previous studies.The first scheme applies staggered frame structure to multi-cell multi-user Massive MIMO system.Under the staggered frame structure,a unique pilot transmission strategy is proposed,in which different users who designate a same cell send pilot signals at different time intervals.In order to improve the capacity of the communication system,Time multiplexing is allowed between different cells,but pilot symbols transmitted by users of different cells in the same time slot need to be orthogonal to each other.Adopting this unique pilot transmission strategy in asynchronous frame structure avoids the pilot pollution problem caused by pilot multiplexing by staggering the transmission time of the same pilot sequence and at the same time carries out the projection processing on the received signal Channel estimation greatly suppresses the channel interference between users and makes the estimation more accurate.In addition,the combination of Matched Filter(MF)detection and channel estimation will greatly reduce the complexity of signal processing.The simulation results show that when using the asynchronous frame structure mentioned in this paper and the special pilot transmission strategy in multi-user multi-cell Massive MIMO and using Orthogonal Projection Least Square(OPLS)method,accurate estimation Performance,improved Subtract Interference Least Square(SILS)methods to reduce complexity also yield more accurate estimates of performance.And then another pilot contamination resolution is shown in Chapter Four.It is based on the beam domain of Massive MIMO channel estimation.By transforming the received signal into a beam domain,the Support Agnostic Bayesian Matching Pursuit(SABMP)algorithm is used to estimate the sparse channel by exploiting the sparse properties of the beam domain channel,so as to eliminate the complexity of orthogonal guidance Frequency design eliminates the need for complex operations such as eigenvalue decomposition and inversion,and does not require inter-cell cooperation.This greatly reduces the complexity while using fewer pilots to solve the problem of pilot contamination.