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Multisample receivers for time-varying channels using particle filtering

  • Stony Brook University
  • University of Wisconsin—Madison

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In the literature it has been reported that multisampling provides an implicit time diversity and that processing more than one sample per symbol results in achieving improved performance over processing a single sample. In this paper we explore this time diversity and develop a novel method for symbol detection from several samples per symbol. The method is based on Bayesian formulation in which we use sequential Monte Carlo filtering, also known as particle filtering. Particle filtering has been applied to data detection problems with a single sample per symbol, and it has shown promising results. The proposed method is developed for communication systems characterized by time-varying channels. We demonstrate via computer simulations that significant performance improvement can be achieved by processing multisamples.

Original languageEnglish
Title of host publication2003 4th IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages565-569
Number of pages5
ISBN (Electronic)078037858X
DOIs
StatePublished - 2004
Event4th IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2003 - Rome, Italy
Duration: Jun 15 2003Jun 18 2003

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2004-January

Conference

Conference4th IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2003
Country/TerritoryItaly
CityRome
Period06/15/0306/18/03

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