Second-order statistics-based blind equalization of IIR single-input multiple-output channels with common zeros
type: Item
instance of: scholarly article
title: Second-order statistics-based blind equalization of IIR single-input multiple-output channels with common zeros
zbMATH Open document ID: 0996.93084
DOI: 10.1109/78.738247
author: Jitendra K. Tugnait
author: Bin Huang
published in: IEEE Transactions on Signal Processing
publication date: 2002-10-27T00:00:00Z
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 94A40
zbMATH DE Number: 1632200
zbMATH Keywords: communication channels
zbMATH Keywords: blind equalization
zbMATH Keywords: antenna arrays
zbMATH Keywords: IIR channels
zbMATH Keywords: common minimum phase zeros
zbMATH Keywords: minimum mean-square error
zbMATH Keywords: second-order statistics
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1109/78.738247
OpenAlex ID: W2148721511
review text: The authors treat the problem of blind equalization of a communication channel with a single input \(w(k)\) and an output vector \({\mathbf y}(k)\) (single input / multiple output or SIMO channel) according to \({\mathbf y}(k)={\mathbf F}(z)w(k)+{\mathbf n}(k)\). For estimating the input \(w(k)\), the noise vector \({\mathbf n}(k)\) is known but not the transfer function \({\mathbf F}(z)\) of the system. Until now, solutions are known with the restrictions that (a) the channel is a FIR system and (b) there are no common zeros among the subchannels. This paper extends these solutions to channels that are IIR with common (minimum phase) zeros. Three algorithms for blind equalization using a MMSE (minimum mean-square error) criterium are described. Only the second-order statistics of the data is required. The results are illustrated by two numerical examples that indicate which of the algorithms works best.
reviewed by: Rüdiger Hoffmann
description: scientific article; zbMATH DE number 1632200