Linear Regression vs. Deep Learning for Signal Quality Monitoring in Coherent Optical Systems
Artikel i vetenskaplig tidskrift, 2022

Error vector magnitude (EVM) is a metric for assessing the quality of m-ary quadrature amplitude modulation (mQAM) signals. Recently proposed deep learning techniques, e.g., feedforward neural networks (FFNNs) -based EVM estimation scheme leverage fast signal quality monitoring in coherent optical communication systems. Such a scheme estimates EVM from amplitude histograms (AHs) of short signal sequences captured before carrier phase recovery (CPR). In this work, we explore further complexity reduction by proposing a simple linear regression (LR) -based EVM monitoring method. We systematically compare the performance of the proposed method with the FFNN-based scheme and demonstrate its capability to infer EVM from an AH when the modulation format information is known in advance. We perform both simulation and experiment to show that the LR-based EVM estimation method achieves a comparable accuracy as the FFNN-based scheme. The technique can be embedded with modulation format identification modules to provide comprehensive signal information. Therefore, this work paves the way to design a fast-learning scheme with parsimony as a future intelligent OPM enabler.

Symbols

Deep learning

Optical modulation

optical performance monitoring

Adaptive optics

Optical signal processing

Optical fibers

error vector magnitude

Monitoring

machine learning

optical fiber communication

Estimation

Författare

Yuchuan Fan

Kungliga Tekniska Högskolan (KTH)

Xiaodan Pang

Kungliga Tekniska Högskolan (KTH)

Aleksejs Udalcovs

RISE Research Institutes of Sweden

Carlos Natalino Da Silva

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Lu Zhang

Zhejiang University

Sandis Spolitis

Riga Technical University

V. Bobrovs

Riga Technical University

Richard Schatz

Kungliga Tekniska Högskolan (KTH)

Xianbin Yu

Zhejiang University

Marija Furdek Prekratic

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Sergei Popov

Kungliga Tekniska Högskolan (KTH)

Oskars Ozolins

Kungliga Tekniska Högskolan (KTH)

IEEE Photonics Journal

19430655 (eISSN)

Vol. 14 4 8643108

Ämneskategorier

Telekommunikation

Kommunikationssystem

Signalbehandling

DOI

10.1109/JPHOT.2022.3193727

Mer information

Senast uppdaterat

2022-09-28