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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Novel Z-Domain Precoding Method for Blind Separation of Spatially Correlated Signals
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Novel Z-Domain Precoding Method for Blind Separation of Spatially Correlated Signals

机译：空间相关信号盲分离的Z域预编码新方法

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摘要

In this paper, we address the problem of blind separation of spatially correlated signals, which is encountered in some emerging applications, e.g., distributed wireless sensor networks and wireless surveillance systems. We preprocess the source signals in transmitters prior to transmission. Specifically, the source signals are first filtered by a set of properly designed precoders and then the coded signals are transmitted. On the receiving side, the Z-domain features of the precoders are exploited to separate the coded signals, from which the source signals are recovered. Based on the proposed precoders, a closed-form algorithm is derived to estimate the coded signals and the source signals. Unlike traditional blind source separation approaches, the proposed method does not require the source signals to be uncorrelated, sparse, or nonnegative. Compared with the existing precoder-based approach, the new method uses precoders with much lower order, which reduces the delay in data transmission and is easier to implement in practice.
机译：在本文中，我们解决了空间相关信号的盲分离问题，这种问题在某些新兴应用（例如分布式无线传感器网络和无线监控系统）中遇到。在传输之前，我们先对发射机中的源信号进行预处理。具体来说，首先通过一组适当设计的预编码器对源信号进行滤波，然后发送编码信号。在接收侧，利用预编码器的Z域特征来分离编码信号，从中恢复源信号。基于所提出的预编码器，导出了一种封闭形式的算法来估计编码信号和源信号。与传统的盲源分离方法不同，该方法不需要源信号不相关，稀疏或非负。与现有的基于预编码器的方法相比，该新方法使用低得多的预编码器，这减少了数据传输的延迟，并且在实践中更易于实现。

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