@inproceedings{5dc6e646b13b4acdaa71e67f29da5a42,
title = "Block adaptive and neural network based digital predistortion and power amplifier performance",
abstract = "The purpose of this paper is to compare the methodology and performance of two different techniques for digital predistortion. The first technique is the block adaptive digital predistorter, which operates using a modified leastmean-squares (LMS) algorithm. The second technique uses a feed-forward time-delay neural network to achieve its linearization performance. The performance of each of these techniques is evaluated for an orthogonal frequency-division multiplexing (OFDM) system with 10dB peak-to-average power ratio (PAR). For easy visual inspection of the tradeoffs, enabling preliminary analysis and teaching, a Java-DSP application has been developed. For more detailed analysis, a clustered MATLAB simulation environment has also been developed. By adding higher-ordered terms as inputs to the neural network, the authors have attained additional linearization near maximum power output for specific power amplifier models.",
keywords = "Block adaptive filters, Linearization, Neural networks, Predistortion, RF amplifier",
author = "Robert Santucci and Andreas Spanias",
year = "2011",
month = jun,
day = "13",
doi = "10.2316/P.2011.721-035",
language = "English (US)",
isbn = "9780889868656",
series = "Proceedings of the 8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2011",
pages = "300--305",
booktitle = "Proceedings of the 8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2011",
note = "8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2011 ; Conference date: 16-02-2011 Through 18-02-2011",
}