Open AccessResearch on linearisation of power amplifier based on digital pre‐distortion
Author(s) -
Fang Kai,
Liu Da,
Wang Yongqing
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0639
Subject(s) - amplifier , distortion (music) , computer science , linearity , electronic engineering , linear amplifier , adjacent channel , nonlinear distortion , convergence (economics) , control theory (sociology) , direct coupled amplifier , rf power amplifier , operational amplifier , engineering , telecommunications , bandwidth (computing) , artificial intelligence , control (management) , economics , economic growth
The power amplifier is an important device in the communication system, and its non‐linear characteristics will lead to serious distortion of the output signal, reducing the performance of the communication system. In order to solve the problem of non‐linearity in a power amplifier, this study proposes an adaptive learning algorithm based on a digital pre‐distortion structure, which combines direct learning and indirect learning structure. It improves the accuracy of pre‐distorter parameter and has the faster convergence speed. The pre‐distortion device parameters are constantly modified to achieve a good linear effect by using the recursive least square adaptive algorithm. The simulation results show that this structure effectively compensates the output signal distortion of the power amplifier, improves the linearisation degree of the power amplifier and reduces the in‐band distortion and adjacent channel leakage ratio.