| Massive multiple-input multiple-output (MIMO) is one of the cutting-edge wireless communication technologies nowdays. By equipping hundreds of antennas at the base station (BS), massive MIMO achieves enormous capacity and high spectral efficiency, this is able to serve more users simultaneously. Even though, the implementation of massive MIMO faces some challenges. Since a large amount of concourrent data streaming happens between the BS and users at the same frequency band, a massive MIMO system usually suffers serious self-interference and effective interference suppression or cancellation technologies are required to fully make use of its potential. Due to the large scale of the system, the channel state information (CSI) exchanges among the decentralized users become difficult. In addition, the signal processing capability of the user terminal is limited. Therefore, relying on the conventional receiver-sider detection only is insufficient for massive MIMO systems. It is necessary to perform the interference cancellation by pre-processing the transmission data at the BS side or by processing the data at both the BS and the user terminals. Based on this background, the precoding technology and the interference alignment (IA) technology for massive MIMO are investigated in this thesis.First, fundamentals of a massive MIMO system are introduced. It includes the state of atr of massive MIMO and the difference between massive MIMO and the traditional single-user MIMO(SU-MIMO) and multiple-user MIMO(MU-MIMO), ome analysis and MATLAB verification of the optimal user number for a massive MIMO system with given BS antenna configuration and finally the theoretical transmission model of a massive MIMO system.Second, the precoding technologies for a time division duplex (TDD) mode massive MIMO are studied. Four classical linear precoding schemes, based on the zero-forcing (ZF) criteria, the block diagonalization (BD) criteria, the minimum mean square error (MMSE) criteria, and the signal leakage noise ratio (SLNR) criteria are expounded in details. The performance analysis and comparison of these schemes are demonstrated via the by MATLAB simulations. Moreover, three typical nonlinear precoding schemes including the dirty paper coding (DPC), the module algebra precoding (THP), and the vector perturbation precoding (VP) are also introduced. The aforementioned precoding technologies are for TDD-mode, where the BS obtains the downlink channel information conveniently by using the channel reciprocity. As for FDD mode, the BS can't take advantage of channel reciprocity anymore. Instead, the BS relies on specific feedback link to obtain the downlink channel state information. To minimize the amount of feedback and simultaneously achieve reliable transmission, this thesis proposes a transmission scheme for FDD-mode massive MIMO system, by combining the joint space division multiplexing (JSDM) technique and a VP precoding techniquer Finally, a joint transmission scheme implemented at the BS and the user terminals is proposed for the TDD-mode massive MIMO system, by using the interference alignment (IA) technique. The performance of the proposed scheme is then thoroughly analyzed. MATLAB simulations show IA technique effectively can eliminates interferences in a massive MIMO system and significantly improves the spectral efficiency (SE) and energy efficiency (EE) of the system.Compared to traditional transmission schemes for massive MIMO systems, the proposed two schemes which are seperately suitable for FDD and TDD massive MIMO systems can effectively improve the spectrum efficiency or energy efficiency. The study has great significance for the next generation of celluar mobile communication technologies which are moving in the direction of higher data rate and lower energy consumption. |
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