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

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.