Novel Z-Domain Precoding Method for Blind Separation of Spatially Correlated Signals

被引:12
|
作者
Xiang, Yong [1 ]
Peng, Dezhong [2 ]
Xiang, Yang [1 ]
Guo, Song [3 ]
机构
[1] Deakin Univ, Sch Informat Technol, Melbourne, Vic 3125, Australia
[2] Sichuan Univ, Coll Comp Sci, Machine Intelligence Lab, Chengdu 610065, Peoples R China
[3] Univ Aizu, Sch Comp Sci & Engn, Fukushima 9658580, Japan
基金
中国国家自然科学基金; 澳大利亚研究理事会;
关键词
Blind source separation; correlated sources; second-order statistics; Z-domain precoding; NONNEGATIVE MATRIX FACTORIZATION; FIR-MIMO-CHANNELS; COMPONENT ANALYSIS; SOURCE EXTRACTION; GRADIENT; INTERNET; DESIGN; ALGORITHMS; MIXTURES; AMPLIFY;
D O I
10.1109/TNNLS.2012.2224671
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码:94 / 105
页数:12
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