Abstract
This paper proposes the adaptive indirect learning architecture (ILA) based digital predistortion (DPD) technique using a recursive prediction error minimization (RPEM) algorithm for linearizing radio frequency (RF) power amplifiers (PAs). The RPEM algorithm allows the forgetting factor to vary with time, which makes the predistorter (PD) parameter estimates more consistent and accurate in steady state, and hence reduces mean square errors. The proposed DPD technique is evaluated with respect to the error vector magnitude (EVM) and the adjacent channel power ratio (ACPR). The simulated PA Wiener model is used to validate the efficiency of the proposed algorithms. The simulation results have confirmed the improvement of the proposed adaptive RPEM ILA based DPD in terms of EVM and ACPR.
This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.02-2016.12.
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Le Duc, H., Nguyen, M.H., Hoang, VP., Nguyen, H.M., Nguyen, D.M. (2019). Linearizing RF Power Amplifiers Using Adaptive RPEM Algorithm. In: Duong, T., Vo, NS., Nguyen, L., Vien, QT., Nguyen, VD. (eds) Industrial Networks and Intelligent Systems. INISCOM 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-030-30149-1_18
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