Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer

Teyan Chen; Yury Zakharov; Chunshan Liu

doi:10.1109/LSP.2011.2148713

Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer

Teyan Chen, Yury Zakharov, Chunshan Liu

Electronic Engineering

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

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.

Original language	English
Article number	5759301
Pages (from-to)	427-430
Number of pages	4
Journal	IEEE Signal Processing Letters
Volume	18
Issue number	7
DOIs	https://doi.org/10.1109/LSP.2011.2148713
Publication status	Published - Jul 2011

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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.",

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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.

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JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

SN - 1070-9908

IS - 7

M1 - 5759301

ER -

Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer

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