Reduced-state MLSD based on volterra kernels for square-law detected multipath channels

Youngsun Ha, Wonzoo Chung

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose a novel reduced-state maximum-likelihood sequence detection (MLSD) structure using the Viterbi algorithm based on the second-order Volterra kernel modeling nonlinear distortion due to square law detection of multipath channels commonly occurring in chromatic dispersion (CD) or polarization mode dispersion (PMD) in optical communication systems. While all existing MLSD methods for square-law detection receivers are based on direct computation of branch metrics, the proposed algorithm provides an efficient and structured way to implement reduced-state MLSD with almost the same complexity of a MLSD for linear channels. As a result, the proposed algorithm reduces the number of parameters to be estimated and the complexity of computation.

Original languageEnglish
Pages (from-to)2315-2325
Number of pages11
JournalKSII Transactions on Internet and Information Systems
Volume5
Issue number12
DOIs
Publication statusPublished - 2011 Dec 31

Keywords

  • Inter symbol interference equalization
  • MLSD
  • Reduced-state MLSD
  • Square law detection
  • Volterra series

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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