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<p>In this paper, we first propose a variable step-size robust normalized subband adaptive filtering (VSS-RNSAF) algorithm. Based on this, for sparse channel estimation, a sparsity-aware VSS-RNSAF (SA-VSS-RNSAF) algorithm is then developed. To reduce the complexity of the SA-VSS-RNSAF, a novel low computational complexity approach is further designed, yielding SA-VSS-RNSAF with low complexity (SA-VSS-RNSAF-LC) algorithm. Finally, the system identification and vehicular echo cancellation experiments demonstrate that the proposed SA-VSS-RNSAF and SA-VSS-RNSAF-LC algorithms outperform the compared competitors in terms of the convergence speed, steady-state error and tracking capability.</p>

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Novel Sparsity-Aware Variable Step-Size Robust Normalized Subband Adaptive Filtering Algorithms for Sparse Channel Estimation

  • 期刊论文

  • 发表日期：

    2025年12月9日

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  • Hongyu Han,
  • Wenting Feng,
  • Sheng Zhang

摘要

In this paper, we first propose a variable step-size robust normalized subband adaptive filtering (VSS-RNSAF) algorithm. Based on this, for sparse channel estimation, a sparsity-aware VSS-RNSAF (SA-VSS-RNSAF) algorithm is then developed. To reduce the complexity of the SA-VSS-RNSAF, a novel low computational complexity approach is further designed, yielding SA-VSS-RNSAF with low complexity (SA-VSS-RNSAF-LC) algorithm. Finally, the system identification and vehicular echo cancellation experiments demonstrate that the proposed SA-VSS-RNSAF and SA-VSS-RNSAF-LC algorithms outperform the compared competitors in terms of the convergence speed, steady-state error and tracking capability.