4.7 Article

Experimental Investigation of Optoelectronic Receiver With Reservoir Computing in Short Reach Optical Fiber Communications

Journal

JOURNAL OF LIGHTWAVE TECHNOLOGY
Volume 39, Issue 8, Pages 2460-2467

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JLT.2021.3049473

Keywords

Chromatic dispersion; direct-detection; reservoir computing; short-reach transmission; signal equalization

Funding

  1. European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant [766115]
  2. European Research Council through the ERCCoG FRECOM Project [771878]
  3. VILLUM FONDEN through the VYI project OPTIC-AI [29344]

Ask authors/readers for more resources

The research offers a solution for low latency and reliable connections in the network of cloud edge data centers, overcoming the main limitation of chromatic dispersion for high symbol rate systems. By utilizing a receiver with shared complexity in optical and digital domains, the goal of achieving 80 km transmission at 32 GBd signal has been successfully demonstrated.
The cloud edge data center will enable reliable and low latency options for the network, and the interconnection among these data-centers will demand a scalable low-complexity scheme. An intensity-modulated and directed detected transmission system is an attractive solution, but chromatic dispersion is the main limitation for higher symbol rate systems. To overcome this challenge, we have proposed and experimentally demonstrated a receiver with shared-complexity between optical and digital domains that enables 80 km transmission reach below KP4 FEC limit for a 32 GBd on-off keying signal. The optical stage consists of optical filters that slices the signal into smaller sub-bands and each is detected by a photodetector. A feedforward neural network and reservoir computing are compared to reconstruct the full signal from the slices and mitigate the chromatic dispersion. Both equalizers have shown similar performance with the advantage of the reservoir computing requiring fewer inputs and easier training process. In this work, we have compared the linear and nonlinear activation functions in the feedforward neural network to investigate the gain of using a nonlinear equalizer. The maximum transmission reach is reduced almost to half, approximate to 45 km, when using the linear. The performance is also reduced if a reduced number of slices is used in the receiver, as we have demonstrated. In this case, using 2 slices to reduce the complexity of the system, instead of the total 4, we have shown a approximate to 55 km transmission reach below KP4 FEC limit. In this work we have also provided a numerical comparison with 4x8 GBd subcarriers system. The results have shown a 40 km increase in transmission reach compared to the proposed optoelectronic system. The trade-off between performance and complexity should be analyzed for each case, as a different hardware is required in each situation.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available