期刊文献+

基于Cholesky分解的MIMO-OFDM系统同信道干扰抑制方法

Cholesky-decompositon-based co-channel interference suppression method in MIMO-OFDM systems
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摘要 在多输入多输出-正交频分复用(MIMO-OFDM)系统中,通过联合估计信道矩阵和干扰协方差矩阵(ICM)的方法来抑制同信道干扰.首先,利用最小二乘法和残差估计方法获取信道矩阵和ICM的初始估计值;然后,基于Cholesky分解方法对ICM的估计值进行改善,并利用改善后的ICM估计值对信道矩阵估计值进行更新.该方法充分利用了时域和频域中的所有可用信息,提高了信道估计精度,较好地抑制了同信道干扰.仿真结果表明:与其他可实现的非迭代方法相比,该方法所得的信道频率响应估计均方误差性能增益高于2 d B;信干噪比(SINR)越大,比特误码率性能的改善程度越好,并且随着天线数的增多,性能增益也增大. For multiple-input multiple-output and orthogonal frequency division multiplexing (MI- MO-OFDM) systems, a method combining the channel matrix with the interference covariance ma- trix (ICM) is developed to suppress co-channel interference. First, the initial estimations of the channel matrix and the ICM are obtained by the least-squares method and the residual error method. Then, the ICM estimation is improved by the Cholesky-decomposition-based method. Finally, the channel matrix estimation is updated by using the improved ICM estimation. In this method, all available knowledge in frequency domain and time domain are exploited to improve the estimation performance and suppress co-channel interference. The simulation results demonstrate that the proposed estimation has over 2 dB better performance than other realizable non-iterative estimations in terms of the mean squared error (MSE) of channel frequency respond (CFR). The larger the signal to interference and noise ratio (SINR), the better the performance improvement in the bit error rate (BER). And with the increase of the number of antennas, performance gain also increases.
出处 《东南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2015年第1期1-4,共4页 Journal of Southeast University:Natural Science Edition
基金 国家自然科学基金资助项目(61320106003 61222102 61201171) 国家高技术研究发展计划(863计划)资助项目(2012AA01A506) 国家科技重大专项课题资助项目(2013ZX03003004 2014ZX03003006) 江苏省"创新团队计划"资助项目 湖南省标准化战略项目资助项目(201200004)
关键词 多输入多输出 正交频分复用 信道估计 同信道干扰 干扰协方差矩阵 multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) channel estimation co-channel interference interference covariance matrix
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参考文献9

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