| Multi-Input and Multi-Output (MIMO) is one of the most important techniques for next generation mobile communications. MIMO can increase capacity of the communication system, and improve the spectral utilization. However, the hardware of the MIMO system is very expensive, which greatly limits its applications. As an important technique in the MIMO system, antenna selection can choose properly one or several best antennas from multiple transmitting and receiving antennas, and reduce the expense with less performance loss. Therefore, the performance-cost-ratio of the MIMO system is improved greatly.In this thesis, the classic algorithms are introduced and analyzed first. Although the optimal algorithm can achieve the highest channel capacity, it is not of practical value because it has a very high complexity. Starting from the Shannon formula and the existing algorithms, a new antenna selection algorithm is proposed through the derivation of mathematical formulas, and its channel capacity is close to that obtained by the optimal algorithm. Simulation results indicate that in the case of 4 transmitting and 8 receiving antennas, choosing 4 antennas to receive signals, the algorithm has a channel capacity close to the capacity obtained by the optimal algorithm. Meanwhile the calculating amount for the addition and multiplication of complex numbers decreases 36.4% and 40.8% respectively. Thus the proposed algorithm converges very fast.The proposed algorithm and Alamouti's Space-Time Block Code (STBC) scheme are used together to analyze its Bit Error Rate (BER). In fact, Alamouti's coding scheme is used at the transmitting end. Meanwhile, at the receiving end, the antenna selection algorithm is used first, and then Alamouti's maximum likelihood decoding scheme is used. Simulation results show that with antenna selection at the receiving end the BER of the proposed algorithm is almost identical with that of the optimal algorithm. Therefore, the proposed algorithm has a better performance. |
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