Efficient Training of Volterra Series-Based Pre-distortion Filter Using Neural Networks
V. Bajaj (TU Delft - Team Gabriel Gleizer, Nokia Bell Labs, Stuttgart)
Mathieu Chagnon (Nokia Bell Labs, Stuttgart)
S. Wahls (TU Delft - Team Gabriel Gleizer)
Vahid Aref (Nokia Bell Labs, Stuttgart)
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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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