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<p>In communication systems, blind equalization algorithms are critical for ensuring the reliability of the system. However, traditional blind equalization algorithms tend to show performance degradation in impulsive noise environments. In order to enhance the robustness of blind equalization algorithms against impulsive noise, this paper presents a Variable Fractional-Order Maximum Versoria Criterion MultiModulus Algorithm (VFOMVC-MMA) for impulsive noise environments. Firstly, the Versoria function is used as the cost function to reduce the complexity of the algorithm, and the idea of MultiModulus Algorithms (MMA) is incorporated into the method to introduce phase information and overcome the phase rotation issue. Moreover, a variable fractional-order updating algorithm is constructed using the Versoria function. The weight vector of the equalizer is updated using a fractional-order gradient search method. This significantly improves the VFOMVC-MMA algorithm’s ability to suppress strong impulsive noise interference and enhances its robustness. Next, the stability and computational complexity of the VFOMVC-MMA are analyzed from a theoretical perspective. Compared with the traditional Maximum Versoria Criterion Constant Modulus Algorithm (MVC-CMA), VFOMVC-MMA accelerates convergence by approximately 50% and reduces the Symbol Error Rate (SER) by about 50%, significantly outperforming other classical algorithms and demonstrating promising application prospects.</p>

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Variable Fractional-Order Maximum Versoria Criterion Multimodulus Blind Equalization Algorithm in Impulsive Noise Environments

  • 期刊论文

  • 发表日期：

    2025年12月9日

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  • Qiang Guo,
  • Na Gong,
  • Mykola Kaliuzhnyi

摘要

In communication systems, blind equalization algorithms are critical for ensuring the reliability of the system. However, traditional blind equalization algorithms tend to show performance degradation in impulsive noise environments. In order to enhance the robustness of blind equalization algorithms against impulsive noise, this paper presents a Variable Fractional-Order Maximum Versoria Criterion MultiModulus Algorithm (VFOMVC-MMA) for impulsive noise environments. Firstly, the Versoria function is used as the cost function to reduce the complexity of the algorithm, and the idea of MultiModulus Algorithms (MMA) is incorporated into the method to introduce phase information and overcome the phase rotation issue. Moreover, a variable fractional-order updating algorithm is constructed using the Versoria function. The weight vector of the equalizer is updated using a fractional-order gradient search method. This significantly improves the VFOMVC-MMA algorithm’s ability to suppress strong impulsive noise interference and enhances its robustness. Next, the stability and computational complexity of the VFOMVC-MMA are analyzed from a theoretical perspective. Compared with the traditional Maximum Versoria Criterion Constant Modulus Algorithm (MVC-CMA), VFOMVC-MMA accelerates convergence by approximately 50% and reduces the Symbol Error Rate (SER) by about 50%, significantly outperforming other classical algorithms and demonstrating promising application prospects.