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Semiblind joint channel estimation and equalization for OFDM systems in rapidly varying channels

机译:快速变化信道中OFDM系统的半盲联合信道估计和均衡

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We describe a new joint iterative channel estimation and equalization algorithm for joint channel estimation and data detection for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and rapidly time-varying channels. The algorithm is based on the expectation maximization-maximum a posteriori (EM-MAP) technique which is very suitable for the multicarrier signal formats. The algorithm leads to a receiver structure that yields the equalized output, using the channel estimates. The pilot symbols are employed to estimate the initial channel coefficients effectively and unknown data symbols are averaged out in the algorithm. The band-limited, discrete cosine serial expansion of low dimensionality is employed to represent the time-varying fading channel. In this way, the resulting reduced dimensional channel coefficients are estimated iteratively with tractable complexity. The extensive computer simulations show that the algorithm has excellent symbol error rate (SER) and mean square error (MSE) performances for very high mobility even during the initialization step.
机译:我们描述了一种新的联合迭代信道估计和均衡算法,用于在存在频率选择和快速时变信道的情况下进行正交频分复用(OFDM)系统的联合信道估计和数据检测。该算法基于期望最大化-最大后验(EM-MAP)技术,该技术非常适合多载波信号格式。该算法导致使用信道估计来产生均衡输出的接收器结构。导频符号被用来有效地估计初始信道系数,并且未知数据符号在算法中被平均。低维的有限带宽,离散余弦序列展开被用来表示随时间变化的衰落信道。以此方式,以易处理的复杂性来迭代地估计所得的减小的维信道系数。大量的计算机仿真表明,该算法具有出色的符号错误率(SER)和均方误差(MSE)性能,即使在初始化步骤中也具有很高的移动性。

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