Long Short Term Memory Neural Network (LSTMNN) and inter-symbol feature extraction for 160 Gbit/s PAM4 from silicon micro-ring transmitter

Ching-Wei Peng,David W.U Chan,Chi-Wai Chow,Tun-Yao Hung,Yin-He Jian,Yeyu Tong,Pin-Cheng Kuo,Guan-Hong Chen,Yang Liu,Chien-Hung Yeh,Hon Ki Tsang

doi:10.1016/j.optcom.2022.129067

Long Short Term Memory Neural Network (LSTMNN) and inter-symbol feature extraction for 160 Gbit/s PAM4 from silicon micro-ring transmitter

Ching-Wei Peng, David W.U Chan + Show 9 more

https://doi.org/10.1016/j.optcom.2022.129067

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Journal: Optics Communications	Publication Date: Oct 22, 2022
Citations: 1

Affiliation: National Yang Ming Chiao Tung University, University of Hong Kong, Feng Chia University

#Short Term Memory Neural Network #Long Short Term Memory Neural Network + Show 8 more

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Abstract

We propose and experimentally illustrate the use of Long Short Term Memory Neural Network (LSTMNN) and inter-symbol feature extraction (IFE) to recover 4-level pulse amplitude modulation (PAM4) data transmitted from a silicon micro-ring modulator (SiMRM) operated at 160 Gbit/s. Pre-hard-decision (HD) forward error correction (FEC) requirement (i.e. bit-error-rate, BER < 3.8 × 10−3) is achieved in the 160 Gbit/s PAM4 signal produced using a 47-GHz bandwidth SiMRM after 1 km single-mode-fiber (SMF) transmission.

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