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About End-to-End Deep Learning of Optical Fiber Communication
This document discusses using deep learning to optimize optical fiber communication systems from end-to-end. Specifically: - It proposes implementing the entire communication system (transmitter, channel, receiver) as a single deep neural network. This allows joint optimization of all components to achieve optimal end-to-end performance. - As a proof-of-concept, it applies this method to an intensity modulation/direct detection system and shows bit error rates below the forward error correction threshold can be achieved. - It models all transmitter/receiver components and the fiber channel within the neural network. The network is trained to minimize symbol error rates for robust transmission over a range of link dispersions. - Results are verified
Detailed Information
| Author: | ['abul_1234'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 13 |
| Language: | English |
| Format: | |
| Price: | FREE |
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