Researches On Channel Estimation And Pilot Coordination In Massive MIMO System Under Pilot Contamination

Multiple-input multiple-output (MIMO) technology has been studied by researchers and widely applied during the last two decades since it can significantly improve the capacity and reliability of wireless systems. However, with the substantial growth in mobile data services, the popularity of mobile terminals and the rapid development of internet, the mobile communication in the future requires higher transmission rate, larger user capacity and higher reliability, which cannot be satisfied by the traditional MIMO technologies.Massive multiple-input multiple-output (Massive MIMO) technology has been proposed by Thomas L. Marzetta in 2010, which refers to the idea that equipping base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple processing. Massive MIMO has obvious advantages compared to the traditional MIMO. However, since the channel coherence time is limited, users in adjacent cells have to use non-orthogonal pilot sequences. This causes pilot contamination and leads to limit the performance of the Massive MIMO system. Therefore, in order to achieve further improvement in performance of Massive MIMO communication system, it is meaningful to research effectively methods to reduce or even eliminate the pilot contamination.Firstly, this thesis introduces the Massive MIMO system model and explains the background of adopting TDD mode. Then analysis on choice of pilot sequence, the classic channel estimation method and downlink transmission link is provided. Moreover the number of users that can be accommodated simultaneously by the Massive MIMO system is discussed. Focusing on the cause of pilot contamination and its impact on system performance, this thesis analyzes the impacts exerted by various factors through simulation.Further, this thesis studies three kinds of channel estimation methods. Bayes channel estimation method utilizes the statistical properties of the channel including large-scale fading, angle of arrival information and so on. The channel estimation method based on eigenvalue decomposition (EVD) and the channel estimation method combined with the iterative least square with projection (ILSP) joint detection algorithm based on EVD make use of the shorter pilot sequence and portion of the received signal. The result of channel estimation is derived in detail, along with the simulation results and comparing analysis of these methods, which show that these methods can reduce pilot contamination effectively.Finally, this thesis analyzes the impact of pilot coordination on the channel estimation performance and gets an optimization approach on pilot coordination. Based on the model of pilot coordination and Bayes channel estimation method, we propose several coordination algorithms to minimize channel estimation error for the goal, including exhaustive algorithm, greedy algorithm based on degradation, greedy algorithm based on channel and random greedy algorithm. Then these algorithms are simulated and compared. We discuss the impacts on channel estimation performance exerted by the number of antennas, angle of arrival and the number of users in each cell. We can see that the coordination algorithms proposed in this thesis are effective to reduce pilot contamination, improve channel estimation accuracy and eventually enhance the performance of the communication system.