dc.contributor |
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.contributor |
Universitat Politècnica de Catalunya. CSC - Components and Systems for Communications Research Group |
dc.contributor.author |
Pham, Thi Quynh Anh |
dc.contributor.author |
Montoro López, Gabriel |
dc.contributor.author |
López Bueno, David |
dc.contributor.author |
Gilabert Pinal, Pere Lluís |
dc.date |
2019-07-03 |
dc.identifier.citation |
Pham, Q.A. [et al.]. Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization. "IEEE transactions on microwave theory and techniques", 3 Juliol 2019, vol. 67, núm. 10, p. 3996-4004. |
dc.identifier.citation |
0018-9480 |
dc.identifier.citation |
10.1109/TMTT.2019.2923186 |
dc.identifier.uri |
http://hdl.handle.net/2117/175534 |
dc.language.iso |
eng |
dc.publisher |
IEEE Microwave Theory and Techniques Society |
dc.relation |
https://ieeexplore.ieee.org/document/8754791 |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.subject |
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
dc.subject |
Mobile communication systems |
dc.subject |
Power amplifiers |
dc.subject |
Principal component analysis |
dc.subject |
Correlation |
dc.subject |
Feature extraction |
dc.subject |
Estimation |
dc.subject |
Matching pursuit algorithms |
dc.subject |
Covariance matrices |
dc.subject |
Peak to average power ratio |
dc.subject |
Amplificadors -- Radiofreqüència |
dc.subject |
Comunicació sense fil, Sistemes de |
dc.title |
Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization |
dc.type |
info:eu-repo/semantics/submittedVersion |
dc.type |
info:eu-repo/semantics/article |
dc.description.abstract |
© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
dc.description.abstract |
This paper presents a new technique that dynamically estimates and updates the coefficients of a digital predistorter (DPD) for power amplifier (PA) linearization. The proposed technique is dynamic in the sense of estimating, at every iteration of the coefficient's update, only the minimum necessary parameters according to a criterion based on the residual estimation error. At the first step, the original basis functions defining the DPD in the forward path are orthonormalized for DPD adaptation in the feedback path by means of a precalculated principal component analysis (PCA) transformation. The robustness and reliability of the precalculated PCA transformation (i.e., PCA transformation matrix obtained off line and only once) is tested and verified. Then, at the second step, a properly modified partial least squares (PLS) method, named dynamic partial least squares (DPLS), is applied to obtain the minimum and most relevant transformed components required for updating the coefficients of the DPD linearizer. The combination of the PCA transformation with the DPLS extraction of components is equivalent to a canonical correlation analysis (CCA) updating solution, which is optimum in the sense of generating components with maximum correlation (instead of maximum covariance as in the case of the DPLS extraction alone). The proposed dynamic extraction technique is evaluated and compared in terms of computational cost and performance with the commonly used QR decomposition approach for solving the least squares (LS) problem. Experimental results show that the proposed method (i.e., combining PCA with DPLS) drastically reduces the amount of DPD coefficients to be estimated while maintaining the same linearization performance. |
dc.description.abstract |
Peer Reviewed |