A Doubly Orthogonal Matching Pursuit Algorithm for Sparse Predistortion of Power Amplifiers

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.