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Sparse Estimation Technique for Digital Pre-distortion of Impedance-Mismatched Power Amplifiers
Circuits, Systems, and Signal Processing ( IF 1.8 ) Pub Date : 2021-02-09 , DOI: 10.1007/s00034-021-01659-z
Cyro S. Hemsi , Cristiano M. Panazio

This paper proposes the application of the Wiener–Hammerstein with feedback (WHFB) model as a digital pre-distortion (DPD) behavioural model for power amplifiers (PA) under load impedance mismatch, since more traditional models suffer performance degradation in this condition. Moreover, this paper proposes the use of the least absolute shrinkage and selection operator (LASSO) approach for the sparse, parsimonious estimation of the WHFB model. Using this technique, the number of coefficients is significantly reduced, thus reducing the DPD running complexity. Additionally, block-oriented LASSO extensions, such as group-LASSO and sparse-group LASSO, are proposed for model dimensioning, i.e. for setting parameters values. Finally, a simplified approximate technique is proposed, in which the most relevant blocks in the model are selected prior to running LASSO, resulting in lower estimation cost. Experimental results demonstrate the ability of the proposed techniques to adequately linearize PAs subject to load impedance mismatch.



中文翻译:

阻抗不匹配功率放大器的数字预失真的稀疏估计技术

本文提出了带有反馈的Wiener-Hammerstein(WHFB)模型作为负载阻抗失配时功率放大器(PA)的数字预失真(DPD)行为模型的应用,因为更多传统模型在这种情况下会导致性能下降。此外,本文提出将最小绝对收缩和选择算子(LASSO)方法用于WHFB模型的稀疏,简约估计。使用这种技术,系数的数量大大减少,从而降低了DPD运行的复杂度。此外,还提出了面向块的LASSO扩展,例如组LASSO和稀疏组LASSO,用于模型标注,即用于设置参数值。最后,提出了一种简化的近似技术,其中,在运行LASSO之前已选择了模型中最相关的模块,从而降低了估算成本。实验结果表明,所提出的技术能够使负载阻抗失配的功率放大器充分线性化。

更新日期:2021-02-09
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