A Doubly Orthogonal Matching Pursuit Algorithm for Sparse Predistortion of Power Amplifiers
A Doubly Orthogonal Matching Pursuit Algorithm for Sparse Predistortion of Power Amplifiers
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DOI：
10.1109/lmwc.2018.2845947
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发表时间：
2018-08-01
影响因子：
3
通讯作者：
Arce, Gonzalo
中科院分区：
文献类型：
--
作者：
Becerra, Juan A.;Madero-Ayora, Maria J.;Arce, Gonzalo
提出了一种基于稀疏行为模型的功率放大器数字预失真方法。Gram-Schmidt正交化被协同地集成到正交匹配追踪算法中，以使所选择的模型回归量与仍待选择的分量去相关。为了验证该算法，在基于15 MHz正交频分复用信号驱动的GaN PA的测试台上进行了实验。在DPD应用中的实验结果和与其他国家的最先进的算法的比较突出了其剪枝能力的增强，减少系数的数量，同时保持性能。
This letter presents a new method for the digital predistortion (DPD) of power amplifiers (PAs) based on sparse behavioral models. The Gram-Schmidt orthogonalization is synergistically integrated into the orthogonal matching pursuit algorithm to decorrelate the selected model regressors against the components still to be selected. Experiments on a test bench based on a GaN PA driven by a 15-MHz orthogonal frequency division multiplexing signal were conducted in order to validate the algorithm. Experimental results in a DPD application and a comparison with other state-of-the-art algorithms highlight the enhancement of its pruning capabilities, reducing the number of coefficients while maintaining the performance.