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

Youngsun Ha; Wonzoo Chung

doi:10.3837/tiis.2011.12.003

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

Youngsun Ha, Wonzoo Chung

Department of Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	2315-2325
Number of pages	11
Journal	KSII Transactions on Internet and Information Systems
Volume	5
Issue number	12
DOIs	https://doi.org/10.3837/tiis.2011.12.003
Publication status	Published - 2011 Dec 31

Keywords

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

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications

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10.3837/tiis.2011.12.003

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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.",

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AB - 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.

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

Abstract

Keywords

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