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Sparse Channel Estimation for Space-Time Block Coded OFDM-Based Underwater Acoustic Channels

机译:基于空时块编码的基于DM的水下声学通道的稀疏信道估计

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Communication over acoustic signals underwater results in multi-scale multi-lag channels due to multipath propagation. Hence, a robust channel estimation technique has to be present at the receiver. In this paper, assuming underwater channels undergoing Rayleigh fading, a path-based channel model that characterizes each path of the time-varying sparse channel by a delay, a Doppler scale, and an attenuation factor is considered. Alamouti's space-time block transmit diversity scheme is used in the form of two transmit antennas and one receiver, and the proposed OFDM-based non-data-aided algorithm iteratively estimates the complex channel parameters of each subcarrier using the expectation maximization (EM) method, which in turn converges to a true maximum a posteriori probability (MAP) estimate of the unknown channel, where the Karhunen-Lo'eve expansion is performed for complexity reduction. Finally, the novel channel estimation algorithm combines the aforementioned MAP-EM technique with ESPRIT for delay estimation by exploiting the sparseness of the underwater acoustic channels. The performance of the proposed algorithm is then presented in terms of average mean square error and symbol error rate for QPSK signaling with extreme Doppler spreads and different pilot spacings. It is shown that excellent mean-square error and symbol error rate performance is achieved even in the presence of extreme Doppler shifts.
机译:由于多径传播,在水下的声信号通信导致多尺度的多滞后信道。因此,必须在接收器处存在稳健的信道估计技术。在本文中,假设经过瑞利衰落的水下信道,考虑通过延迟,多普勒尺度和衰减因子表征时变稀疏信道的每个路径的基于路径的信道模型。 Alamouti的空间时间块发射分集方案用于两个发射天线和一个接收器的形式,并且所提出的基于OFDM的非数据辅助算法使用期望最大化(EM)方法迭代估计每个子载波的复杂信道参数,这反过来会收敛到未知信道的真实最大概率(地图)估计,其中对复杂性降低进行Karhunen-Lo'eve扩展。最后,通过利用水下声道的稀疏来利用水下声道的稀疏来将上述地图-EM技术与ESPRIT结合了上述地图-EM技术。然后以具有极端多普勒扩散和不同的导频间距的QPSK信号传导的平均平均误差和符号误差率和不同的导频间隔的平均均方误差和符号误差率的性能。结果表明,即使在存在极端多普勒班次的情况下,也可以实现优异的平均误差和符号错误率性能。

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