Variable forgetting factor LS algorithm for polynomial channel model
type: Item
instance of: scholarly article
title: Variable forgetting factor LS algorithm for polynomial channel model
zbMATH Open document ID: 1214.94039
DOI: 10.5402/2011/915259
author: Amit Kumar Kohli
author: Amrita Rai
author: Meher Krishna Patel
published in: ISRN Signal Processing
publication date: 2011-03-22T00:00:00Z
review text: Summary: Variable forgetting factor (VFF) least squares (LS) algorithm for polynomial channel paradigm is presented for improved tracking performance under nonstationary environment. The main focus is on updating VFF when each time-varying fading channel is considered to be a first-order Markov process. In addition to efficient tracking under frequency-selective fading channels, the incorporation of proposed numeric variable forgetting factor (NVFF) in LS algorithm reduces the computational complexity.
Mathematics Subject Classification ID: 94A40
zbMATH DE Number: 5869000
Wikidata QID: Q58690131
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.5402/2011/915259
OpenAlex ID: W2025649970
cites work: Tracking of time-varying channels using two-step LMS-type adaptive algorithm
description: scientific article; zbMATH DE number 5869000