用于MIMO-OFDM無線通信系統(tǒng)的一種新的自適應半盲波束形成算法
A Novel Adaptive Semi-blind Beamforming Algorithm for MIMO-OFDM Wireless Communication Systems
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摘要: 該文根據(jù)MIMO-OFDM物理層結構和無線移動矩陣信道的特性，從神經(jīng)網(wǎng)絡和信息論觀點詳細推導了一種新的多天線陣列自適應半盲波束形成器算法。與常規(guī)的盲估計和導頻輔助信道估計算法不同的是，本文提出的新的半盲算法在權矢量自適應更新時，不斷地用基于導頻估計的權矢量進行修正。最后，用實際的HIPERLAN2協(xié)議進行了計算機仿真。結果表明這種算法不增加發(fā)射信號功率和不占用額外帶寬，能提高天線增益性能和有效地提取出期望的發(fā)射信號，在收斂速度和BER性能方面優(yōu)于常規(guī)的導頻輔助信道估計算法。該波束形成器能自適應調(diào)整權矢量，其更新方式與TDMA和CDMA相似，所以本算法可直接用于有天線陣列的基于OFDM的第三代(3G)和三代后(3G beyond)的無線通信系統(tǒng)。Abstract: In this paper a novel adaptive semi-blind beamforming algorithm is proposed for OFDM-MIMO systems. First the nonlinear neural networks combined with maximized mutual information rule are used for estimating the coarse weights of beamformer, then the beamforming algorithm adaptively adjusts the vector weights by means of the known pilot tones inserted into the frame structure, thus the channel equalization can be further im-proved. The proposed algorithm is compared to two other channel estimators under various multipath fading environments through simulations and experimental data. The results show that the semi-blind beamforming algorithm has much better overall performance in terms of BER, moreover has high aperture gains with very good directivity in the beamformer pattern.
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