Abstract
We present a neural network-based nonlinear electronic feed-forward equalizer. It compensates for the chromatic dispersion (CD) distortions in fiber optic communication systems with direct photo-detection. The proposed equalizer achieves bit error rate (BER) performance comparable to the maximum-likelihood sequence estimator (MLSE), with significantly lower computational cost. The complexity of the introduced equalizer scales linearly with the length of the inter-symbol interference (ISI) as opposed to exponential growth the MLSE complexity.
| Original language | English |
|---|---|
| Title of host publication | 2018 International Applied Computational Electromagnetics Society Symposium in Denver, ACES-Denver 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9780996007870 |
| DOIs | |
| State | Published - 23 May 2018 |
| Externally published | Yes |
Publication series
| Name | 2018 International Applied Computational Electromagnetics Society Symposium in Denver, ACES-Denver 2018 |
|---|
Bibliographical note
Publisher Copyright:© 2018 Applied Computational Electromagnetics Society (ACES).
ASJC Scopus subject areas
- Computer Networks and Communications
- Computational Mathematics
- Numerical Analysis
- Instrumentation
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