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Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer

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Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer. / Chen, Teyan; Zakharov, Yury; Liu, Chunshan.

In: IEEE Signal Processing Letters, Vol. 18, No. 7, 5759301, 07.2011, p. 427-430.

Research output: Contribution to journalLetterpeer-review

Harvard

Chen, T, Zakharov, Y & Liu, C 2011, 'Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer', IEEE Signal Processing Letters, vol. 18, no. 7, 5759301, pp. 427-430. https://doi.org/10.1109/LSP.2011.2148713

APA

Chen, T., Zakharov, Y., & Liu, C. (2011). Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer. IEEE Signal Processing Letters, 18(7), 427-430. [5759301]. https://doi.org/10.1109/LSP.2011.2148713

Vancouver

Chen T, Zakharov Y, Liu C. Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer. IEEE Signal Processing Letters. 2011 Jul;18(7):427-430. 5759301. https://doi.org/10.1109/LSP.2011.2148713

Author

Chen, Teyan ; Zakharov, Yury ; Liu, Chunshan. / Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer. In: IEEE Signal Processing Letters. 2011 ; Vol. 18, No. 7. pp. 427-430.

Bibtex - Download

@article{c2eb57658b3e496099b2343ca3914661,
title = "Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer",
abstract = "In this letter, we propose a low-complexity channel-estimate based adaptive linear equalizer. The equalizer exploits coordinate descent iterations for computation of equalizer coefficients. The proposed technique has as low complexity as operations per sample, where and are the equalizer and channel estimator length, respectively, and is the number of iterations such that and . Moreover, with dichotomous coordinate descent iterations, the computation of equalizer coefficients is multiplication-free and division-free, which makes the equalizer attractive for hardware design. Simulation shows that the proposed adaptive equalizer performs close to the minimum mean-square-error equalizer with perfect knowledge of the channel.",
author = "Teyan Chen and Yury Zakharov and Chunshan Liu",
year = "2011",
month = jul,
doi = "10.1109/LSP.2011.2148713",
language = "English",
volume = "18",
pages = "427--430",
journal = "IEEE Signal Processing Letters",
issn = "1070-9908",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "7",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer

AU - Chen, Teyan

AU - Zakharov, Yury

AU - Liu, Chunshan

PY - 2011/7

Y1 - 2011/7

N2 - In this letter, we propose a low-complexity channel-estimate based adaptive linear equalizer. The equalizer exploits coordinate descent iterations for computation of equalizer coefficients. The proposed technique has as low complexity as operations per sample, where and are the equalizer and channel estimator length, respectively, and is the number of iterations such that and . Moreover, with dichotomous coordinate descent iterations, the computation of equalizer coefficients is multiplication-free and division-free, which makes the equalizer attractive for hardware design. Simulation shows that the proposed adaptive equalizer performs close to the minimum mean-square-error equalizer with perfect knowledge of the channel.

AB - In this letter, we propose a low-complexity channel-estimate based adaptive linear equalizer. The equalizer exploits coordinate descent iterations for computation of equalizer coefficients. The proposed technique has as low complexity as operations per sample, where and are the equalizer and channel estimator length, respectively, and is the number of iterations such that and . Moreover, with dichotomous coordinate descent iterations, the computation of equalizer coefficients is multiplication-free and division-free, which makes the equalizer attractive for hardware design. Simulation shows that the proposed adaptive equalizer performs close to the minimum mean-square-error equalizer with perfect knowledge of the channel.

UR - http://www.scopus.com/inward/record.url?scp=79958757885&partnerID=8YFLogxK

U2 - 10.1109/LSP.2011.2148713

DO - 10.1109/LSP.2011.2148713

M3 - Letter

VL - 18

SP - 427

EP - 430

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

SN - 1070-9908

IS - 7

M1 - 5759301

ER -