Orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm for fractional tap-spaced adaptive MLSE equalizers

Satoshi Denno; Yoichi Saito

doi:10.1109/26.780451

Orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm for fractional tap-spaced adaptive MLSE equalizers

Satoshi Denno, Yoichi Saito

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

1 Citation (Scopus)

Abstract

A fast channel-estimation scheme for adaptive maximum-likelihood sequence-estimation (MLSE) equalizers called the orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm is proposed. This algorithm requires only as many operations as the least mean squares algorithm in spite of its excellent performance. Furthermore, operational complexity reduction method is proposed in which the orthogonal matrix is reconfigured as eigenvectors with valid eigenvalues. The OVLMS algorithm is theoretically analyzed and is shown to have both fast acquisition and good tracking performance. An equalizer using OVLMS (OVLMS-MLSE) experimentally attains a 5-dB improvement in bit-error rate (BER) performance at BER of 1.0 × 10^-4 over coherent detection. The OVLMS-MLSE is found to be free of the degradation caused by sampling phase error. Finally, the OVLMS-MLSE equalizer is experimentally verified to synchronize within five symbols.

Original language	English
Pages (from-to)	1151-1160
Number of pages	10
Journal	IEEE Transactions on Communications
Volume	47
Issue number	8
DOIs	https://doi.org/10.1109/26.780451
Publication status	Published - 1999
Externally published	Yes

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/26.780451

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title = "Orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm for fractional tap-spaced adaptive MLSE equalizers",

abstract = "A fast channel-estimation scheme for adaptive maximum-likelihood sequence-estimation (MLSE) equalizers called the orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm is proposed. This algorithm requires only as many operations as the least mean squares algorithm in spite of its excellent performance. Furthermore, operational complexity reduction method is proposed in which the orthogonal matrix is reconfigured as eigenvectors with valid eigenvalues. The OVLMS algorithm is theoretically analyzed and is shown to have both fast acquisition and good tracking performance. An equalizer using OVLMS (OVLMS-MLSE) experimentally attains a 5-dB improvement in bit-error rate (BER) performance at BER of 1.0 × 10-4 over coherent detection. The OVLMS-MLSE is found to be free of the degradation caused by sampling phase error. Finally, the OVLMS-MLSE equalizer is experimentally verified to synchronize within five symbols.",

author = "Satoshi Denno and Yoichi Saito",

year = "1999",

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T1 - Orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm for fractional tap-spaced adaptive MLSE equalizers

AU - Denno, Satoshi

AU - Saito, Yoichi

PY - 1999

Y1 - 1999

N2 - A fast channel-estimation scheme for adaptive maximum-likelihood sequence-estimation (MLSE) equalizers called the orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm is proposed. This algorithm requires only as many operations as the least mean squares algorithm in spite of its excellent performance. Furthermore, operational complexity reduction method is proposed in which the orthogonal matrix is reconfigured as eigenvectors with valid eigenvalues. The OVLMS algorithm is theoretically analyzed and is shown to have both fast acquisition and good tracking performance. An equalizer using OVLMS (OVLMS-MLSE) experimentally attains a 5-dB improvement in bit-error rate (BER) performance at BER of 1.0 × 10-4 over coherent detection. The OVLMS-MLSE is found to be free of the degradation caused by sampling phase error. Finally, the OVLMS-MLSE equalizer is experimentally verified to synchronize within five symbols.

AB - A fast channel-estimation scheme for adaptive maximum-likelihood sequence-estimation (MLSE) equalizers called the orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm is proposed. This algorithm requires only as many operations as the least mean squares algorithm in spite of its excellent performance. Furthermore, operational complexity reduction method is proposed in which the orthogonal matrix is reconfigured as eigenvectors with valid eigenvalues. The OVLMS algorithm is theoretically analyzed and is shown to have both fast acquisition and good tracking performance. An equalizer using OVLMS (OVLMS-MLSE) experimentally attains a 5-dB improvement in bit-error rate (BER) performance at BER of 1.0 × 10-4 over coherent detection. The OVLMS-MLSE is found to be free of the degradation caused by sampling phase error. Finally, the OVLMS-MLSE equalizer is experimentally verified to synchronize within five symbols.

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Orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm for fractional tap-spaced adaptive MLSE equalizers

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