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SCFNN-Based Decision Feedback Equalization Robust to Frequency Offset and Phase Noise

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Abstract

This paper proposes a self-constructing fuzzy neural network-based decision feedback equalizer (SCFNN DFE). An online learning algorithm containing the structure and parameter learning phases is employed in training the SCFNN DFE. Specifically, the feedforward input vector classification and a gradient-descent method are both used in this online learning algorithm. We show by simulations that the proposed SCFNN DFE offers improvement compared to the traditional DFE methods in the presence of frequency offset and phase noise.

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Authors and Affiliations

  1. Department of Communication Engineering, National Central University, Chung Li, Taoyuan, 32054, Taiwan, ROC

    Yao-Jen Chang & Chia-Lu Ho

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  1. Yao-Jen Chang
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  2. Chia-Lu Ho
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Correspondence to Yao-Jen Chang.

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Chang, YJ., Ho, CL. SCFNN-Based Decision Feedback Equalization Robust to Frequency Offset and Phase Noise. Circuits Syst Signal Process 30, 929–940 (2011). https://doi.org/10.1007/s00034-010-9258-5

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  • DOI: https://doi.org/10.1007/s00034-010-9258-5

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