Novel Z-domain precoding method for blind separation of spatially correlated signals

Yong Xiang, Dezhong Peng, Yang Xiang, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)94-105
Number of pages12
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume24
Issue number1
DOIs
Publication statusPublished - 8 Oct 2013
Externally publishedYes

Keywords

  • Blind source separation
  • Correlated sources
  • Second-order statistics
  • Z-domain precoding

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this