A new adaptive turbo equalizer with soft information classification

Kyeongyeon Kim, Jun Won Choi, Andrew C. Singer, Kyungtae Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Linear turbo equalizers with/without channel estimation have been exploited due to their good performance with low complexity compared to a maximuma posteriori (MAP) turbo equalizer. Much work has focused on channel estimate-based minimum mean square error (MMSE) turbo equalizers. However, an MMSE turbo equalizer still requires higher complexity than an adaptive turbo equalizer such as with a normalized least mean square (NLMS) turbo equalizer. Even if adaptive turbo equalizers converge, there is often a performance loss compared to an MMSE turbo equalizer because the adaptive turbo equalizers treat soft decision data as stationary. In order to reduce this loss, we propose a new adaptive turbo equalizer that uses the soft decision data to switch among a set of K different equalizers to approximate the time varying MMSE behavior. Simulations show that the proposed switching-based NLMS turbo equalizer has better bit error rate (BER) performance than a conventional NLMS turbo equalizer by as much as 0.6dB.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3206-3209
Number of pages4
ISBN (Print)9781424442966
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Country/TerritoryUnited States
CityDallas, TX
Period3/14/103/19/10

Keywords

  • Adaptive filters
  • Classification
  • MMSE
  • NLMS
  • Turbo equalization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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