| As one of the beyond4G (Generation) or5G candidates for key techniques, Massive MIMO (Multiple-Input Multiple-Output) receives abroad attention and research. Massive MIMO refers to that the base station installs tens of or hundreds of antennas, simultaneously serves tens of mobile terminals, and employs TDD (time-division duplex operation). Research results show that Massive MIMO has super frequency efficiency and energy efficiency, and Massive MIMO also can greatly improve overall capacity and suppress inter-cell and intra-cell interference.Considering the excessive energy consumption in future mobile communication systems, energy efficiency must be one of research hot spots of Massive MIMO. This thesis proposes a high energy efficiency antenna selection algorithm. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals are jointly optimized to maximize energy efficiency. In consideration of the complexity of joint optimization, this thesis gives a step by step optimization algorithm, which is equivalent to joint optimization. Simulation result demonstrates the equivalence, either.As we all know, pilot contamination is a primary issue of Massive MIMO system, it is this obstacle that limits the performance of Massive MIMO system. The fundamental reason of pilot contamination is that users in different cells use the same frequency, pilot sequence and simultaneous transmission. To cell-edge users, the effect of pilot contamination is more serious. Therefore, this thesis proposes an algorithm to enhance the performance of cell-edge user. By using fractional frequency reuse, this algorithm can significantly mitigate pilot contamination. Compared with the method that the reuse factor equal to one, simulation results of the proposed algorithm show cell-edge users has a considerable increase in signal to interference ratio and capacity. |
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