Efficient Training of Volterra Series-Based Pre-distortion Filter Using Neural Networks

Conference paper (2022)

Authors

V. Bajaj Team Sander Wahls - Mechanical, Maritime and Materials Engineering , Nokia Bell Labs, Stuttgart
Mathieu Chagnon Nokia Bell Labs, Stuttgart
S. Wahls Team Sander Wahls - Mechanical, Maritime and Materials Engineering
Vahid Aref Nokia Bell Labs, Stuttgart
Research Group
Team Sander Wahls (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Sander Wahls

Abstract

We present a simple, efficient “direct learning” approach to train Volterra series-based pre-distortion filters using neural networks. We show its superior performance over conventional training methods using a 64-QAM 64 GBaud simulated transmitter with varying transmitter nonlinearity and noisy conditions.

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