Modulation Format Identification of Optical Signals: AnApproach Based on Singular Value Decomposition ofStokes Space Projections
2020
In this paper, two Stokes space (SS) analysis schemes for modulation
format identification (MFI) are proposed. These schemes are based on
singular value decomposition (SVD) and Radon transform (RT) for feature
extraction. The singular values (SVs) are extracted from the SS
projections for different modulation formats to discriminate between them.
The SS projections are obtained at different optical signal-to-noise
ratios (OSNRs) ranging from 11 to 30 dB for seven dual-polarized
modulation formats. The first scheme depends on the SVDs of the SS
projections on three planes, while the second scheme depends on the SVDs
of the RTs of the SS projections. Different classifiers including support
vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN) for
MFI based on the obtained features are used. Both simulation and
experimental setups are arranged and tested for proof of concept of the
proposed schemes for the MFI task. Complexity reduction is studied for the
SVD scheme by applying the decimation of the projections by two and four
to achieve an acceptable classification rate, while reducing the
computation time. Also, the effect of the variation of phase noise (PN)
and state of polarization (SoP) on the accuracy of the MFI is considered
at all OSNRs. The two proposed schemes are capable of identifying the
polarization multiplexed modulation formats blindly with high accuracy
levels up to 98%, even at low OSNR values of 12 dB, high PN levels up to
10 MHz, and SoP up to 45°.
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
24
References
3
Citations
NaN
KQI