Analysing digital predistortion technique for computation‐efficient power amplifier linearisation in the presence of measurement noise

The noise is an inherent part of a transceiver system, which becomes more severe on low‐cost systems. The power amplifier (PA) further enhances this noise and the signal to be propagated to the receiver. The conventional approach of digital predistortion (DPD) assumes an ideal transceiver system whi...

Full description

Saved in:
Bibliographic Details
Published inIET science, measurement & technology Vol. 15; no. 4; pp. 398 - 410
Main Authors Tripathi, Girish Chandra, Rawat, Meenakshi
Format Journal Article
LanguageEnglish
Published Wiley 01.06.2021
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The noise is an inherent part of a transceiver system, which becomes more severe on low‐cost systems. The power amplifier (PA) further enhances this noise and the signal to be propagated to the receiver. The conventional approach of digital predistortion (DPD) assumes an ideal transceiver system while extracting data for the predistortion function generation. As a result, performance limitation arises due to residual signal–noise interaction. This study presents the accuracy and implementation issues of DPD on a low‐cost transceiver having lower bit resolution in the presence of transceiver noise. Different model architectures, as well as processing algorithms, are compared in terms of numerical stability of the solution (condition number of observation matrix), efficient field‐programmable gate array (FPGA) implementation (dispersion of coefficients, in‐band model performance (normalised mean square error), and out‐of‐band model performance (adjacent channel power ratio). The simulation results are tested on FPGA and direct conversion transceiver‐based platform using PA. A long‐term evolution signal with 64 quadrature amplitude modulation is used for performance evaluation. The suitability of the various polynomial models for fixed‐point implementation and the required memory size for implementing the DPD model is further established.
ISSN:1751-8822
1751-8830
DOI:10.1049/smt2.12041