Low-Complexity Channel-Estimate Based Adaptive Linear Equalizer

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...

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Veröffentlicht in:IEEE signal processing letters 2011-07, Vol.18 (7), p.427-430
Hauptverfasser: Teyan Chen, Zakharov, Yuriy V, Chunshan Liu
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2011.2148713