Nonlinear neural network equalizer for metro optical fiber communication systems

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

doi:10.23919/ropaces.2018.8364214

Cited by 2 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Machine learning has become popular and has attracted increasing attention from optical communities. Because of their powerful feature extraction and analysis capabilities, neural networks (NNs) have been applied into signal equalization and nonlinear compensation [23][24][25][26]. Elias Giacoumidis experimentally demonstrated about 2 dB quality factor (Q-factor) enhancement in terms of fiber nonlinearity compensation using an artificial neural network (ANN) for 40 Gb/s 16 quadrature amplitude modulation (16-QAM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) at 2000 km of uncompensated standard single-mode fiber (SSMF) transmission [27].…”

Section: Introductionmentioning

confidence: 99%

137 Gb/s PAM-4 Transmissions at 850 nm over 40 cm Optical Backplane with 25 G Devices with Improved Neural Network-Based Equalization

et al. 2019

View full text Add to dashboard Cite

An improved neural network-based equalization method is proposed and experimentally demonstrated. The up-to-137 Gb/s transmission of four level pulse amplitude modulation (PAM-4) signals with 25 G class 850 nm optical devices is achieved over an in-house fabricated 40 cm optical backplane. An in-depth investigation is conducted regarding the impact of delayed taps and spans on equalization performance. A performance comparison of the proposed method with the traditional maximum likelihood sequence estimation (MLSE) and decision feedback equalization (DFE) is also undertaken. For the bit rate from 80 to 100 Gb/s, the proposed method achieves an adopted hard-decision forward error correction (HD-FEC) requirement at a received optical power (RoP) of −9 and −8 dBm, while DFE and MLSE cannot meet the HD-FEC requirement. When the bit rate increases from 120 to 137 Gb/s, the proposed equalization method still successfully maintains the acceptable system performance at an RoP of −4 and −2.5 dBm. Furthermore, the specific bit error rate (BER) performances for varied maximum achievable bit rate under different RoPs by applying MLSE and the proposed method are also analyzed. This provides an important potential solution to realize the future data centers.

show abstract