Model Identification for Digital Predistortion of Power Amplifier With Signed Regressor Algorithm

摘要

In this letter, a low-complexity approach is proposed to estimate model parameters of digital predistortion (DPD). It takes the advantage of low implementation cost of the signed regressor algorithm and eliminates most multiplications required. A Walsh-Hadamard transform is employed to avoid the correlation between signed DPD basis functions. Performance of the proposed approach is evaluated via experiments, with a two-carrier long term evolution-advanced signal on a 3.5-GHz power amplifier. It is shown that compared with the conventional least-square-based method the proposed approach can achieve similar linearization and convergence performance with much lower computational complexity.