Low-complexity channel-estimate based adaptive linear equalizer

Teyan Chen*, Yuriy V. Zakharov, Chunshan Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


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 O(Nu(K+M)) operations per sample, where K and M are the equalizer and channel estimator length, respectively, and Nu is the number of iterations such that Nu ≪ K and Nu ≪ M. 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 languageEnglish
Article number5759301
Pages (from-to)427-430
Number of pages4
JournalIEEE Signal Processing Letters
Issue number7
Publication statusPublished - 2011
Externally publishedYes


  • Adaptive equalization
  • channel estimation
  • DCD
  • dichotomous coordinate descent
  • linear equalizer


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