300-Gbit/s/λ 8-Level Pulse-Amplitude-Modulation (PAM8) with a silicon microring modulator utilizing long short term memory regression and deep neural network classification

Tun Yao Hung, David W.U. Chan, Ching Wei Peng, Chi Wai Chow*, Hon Ki Tsang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We present the first experimental demonstration up the authors' knowledge a high-capacity short-reach optical communication link which employs a long-short-term-memory (LSTM) and deep-neural-network (DNN) for enabling 300-Gbit/s (100 Gbaud) 8-level pulse amplitude modulation (PAM8) generated by a single 55-GHz bandwidth silicon microring modulator (SiMRM) with a driving voltage of 1.8-Vpp. As PAM8 modulation has a lower average level-to-level transition energy when compared with that in PAM4, it could be possible to achieve higher energy efficiency when utilizing PAM8 at the same driving voltage. To recover the PAM8 modulation, LSTM and DNN are utilized for regression and classification respectively. The LSTM contains memory cells for dealing with signal time domain dependencies, and has the ability to store, read, and reject data passing through the neural network. The subsequent DNN performs the classification of the 8 levels. Experimental results show that 300 Gbit/s PAM8 modulation is achieved at back-to-back (B2B) and 270 Gbit/s PAM8 is achieved after 1 km standard single-mode-fiber (SSMF) transmission satisfying the soft-decision forward error correction (SD-FEC) bit-error-rate requirement (BER) of 2.4 × 10-2.

Original languageEnglish
Article number110379
JournalOptics and Laser Technology
Volume171
DOIs
StatePublished - Apr 2024

Keywords

  • Deep Neural Network
  • Long Short Term Memory (LSTM)
  • Pulse amplitude modulation (PAM)
  • Silicon photonics

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