Fast channel impulse response estimation scheme for adaptive maximum likelihood sequence estimation equalizer - Proposal of variable-gain least mean square algorithm

Satoshi Denno, Yoichi Saito

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper discusses the channel estimation algorithm in the adaptive maximum likelihood sequence estimation (MLSE) and proposes the variable-gain least square (VLMS) algorithm that can realize a fast acquisition by a simple configuration. When the sent code is a random sequence, VLMS is represented by a deterministic canonical equation based on the fact that a deterministic autocorrelation matrix for VLMS can be diagonalized. It is shown that VLMS can be realized with nearly the same computational complexity as least-mean square (LMS) algorithm. It is shown theoretically by analysis that VLMS can realize the same fast acquisition and tracking characteristics as those of the recursive least square (RLS) algorithm. An algorithm also is derived which is an extension of the basic idea of VLMS and can be used for the fractional MLSE equalizer. It is shown experimentally that the fractional MLSE equalizer with VLSE algorithm can compensate the performance deterioration due to the sampling phase error. In the two-wave Rayleigh fading environment with faT = 4.0 × 10-4, the floor error can be suppressed below 10-4. It is shown also experimentally that the proposed equalizer has an excellent synchronization performance in which the initial acquisition can be completed in approximately six symbols.

Original languageEnglish
Pages (from-to)104-115
Number of pages12
JournalElectronics and Communications in Japan, Part I: Communications (English translation of Denshi Tsushin Gakkai Ronbunshi)
Volume79
Issue number7
DOIs
Publication statusPublished - Jul 1996
Externally publishedYes

Keywords

  • Channel estimation
  • Fast acquisition
  • Fractional sample
  • MLSE
  • Reduction of computational complexity

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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