LAUSR

Digital predistortion (DPD) of broadband power amplifiers (PAs) requires a large number of parameters to compensate for the severe nonlinear distortion, which may cause considerable computational complexity in the DPD parameter identification process. To solve this problem, we proposed a novel signed orthogonal regressor algorithm (SORA) to simplify the identification of DPD parameters. Based on the signed regressor algorithm and principal component analysis (PCA), the proposed algorithm can eliminate most of the multiplication operations in the identification process and greatly reduce the computational complexity. Furthermore, the proposed SORA is modified to be able to estimate each parameter independently. Experimental results show that compared with the conventional PCA-based method, the proposed two methods can realize comparable linearization performance with significantly lower computational complexity.