A Study On Channel Estimation And Pilot Allocation Technology In Massive MIMO

Multiple Input Multiple Output(MIMO)technology has brought significant improvements in reliability and capacity to wireless communication systems,and has received extensive attention and research over the past two decades.However,with the development of wireless communication devices and the advance of multimedia service demand,future mobile communication requires faster transmission speed and higher reliability,but conventional MIMO cannot meet the requirements.Massive MIMO technology provides a significant advantage over traditional MIMO by arranging a large number of antennas at the base station to achieve several times higher spectral efficiency and energy efficiency after simple processing.However,since the channel coherence time is limited,the neighboring cells have the same pilot,which may cause the target cell to receive signals to be interfered by the pilot contamination,further affecting the accuracy of pilot-based channel estimation.On the other hand,the high complexity of traditional estimation methods in channel estimation also affects the applicability of the estimation algorithm.Therefore,the research on reducing pilot contamination and reducing the complexity of channel estimation algorithm in Massive MIMO is the key to improve system performance and practicability.The main research contents of this paper are as follows:Firstly,this paper studies Massive MIMO system model and TDD communication mode,the orthogonal characteristics of the pilot,the traditional pilot allocation form,and the form of pilot allocation aiming at user fairness and rate maximization.The allocation problem is modeled as an optimization problem which solution is explained in detail,and the classical optimization search algorithms is discussed.Finally,two traditional estimation algorithms in chanmel estimation are described separately.Secondly,two pilot allocation schemes are proposed for multi-cell systems in Massive MIMO.The proposed scheme is based on the optimization problem of maxirmizing system rate.The first scheme is based on the allocation of greedy tabu search algorithls.The second scheme takes into account the global search and local search capabilities by using the competitive algorithms,which greatly improves system perforaiance,and reduces the complexity of algorithm while the number of users in the system increases.The simulation results can demonstrate the efifectiveness of the two algorithms in improving system rate and improving estimation accuracy of channel estimation.Finally,researching on pilot-based channel estimation in Massive MIMO multi-cell systems,a channel estimation scheme based on biconjugate gradient stabilized algorithm is proposed.Firstly,the classical Bayesian MMSE estimation model is introduced,and the high complexity problem caused by matrix inversion operation in the algorithm is analyzed.By transforming the inversion operation into solving linear eqpations,the biconjugate gradient stabilized algorithm is used to calculate the estimation matrix.The performance of the proposed algorithm based on the conjugate gradient algorithm approaches to the traditional bayesian MMSE algorithm,which complexity is reduced from O(M3)toO(M2),where jM is the product of the nrnnber of transmitting and receiving antennas.The simulation results show that the proposed algorithm reducing complexity with lower performance loss,and suitable for scenes with pilot contamination.