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Optimal design of NLMS algorithm with a variable scaler against impulsive interference

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Abstract

This study proposes a scaler for the normalized least-mean-square algorithm, which is derived based on a cost function designed to retain robustness to a sudden change. A novel step-size updating strategy is designed to improve the tracking speed when the system encounters an impulsive interference. We illustrate that the proposed method is effective for abruptly changed systems with both colored noises and white Gaussian noises. In particular, we perform the theoretical analysis for steady-state excess mean square error based on a Taylor expansion approach. Several representative scaler-based adaptive algorithms are performed in impulsive interference environments for comparisons, including system identification and system tracking. Simulations and echo cancellation experiment are conducted to demonstrate the improvement of the proposed method and support the theoretical analysis.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Project No. 62171369, 61701405).

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Authors and Affiliations

  1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China

    Fei-Yun Wu & Yan-Chong Song

  2. Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi’an, Shaanxi, China

    Fei-Yun Wu & Yan-Chong Song

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  1. Fei-Yun Wu
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  2. Yan-Chong Song
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Correspondence to Fei-Yun Wu.

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Wu, FY., Song, YC. Optimal design of NLMS algorithm with a variable scaler against impulsive interference. SIViP 17, 2705–2712 (2023). https://doi.org/10.1007/s11760-023-02487-1

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