Modulation format identification based on phase statistics in Stokes space

Wang, Maochun; Liu, Jie; Zhang, Junwei; Zhang, Dongpeng; Guo, Changjian

doi:10.1016/j.optcom.2020.126481

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Non-data-aided schemes can be further roughly divided into schemes based on Stokes space and schemes based on the signal equalized by the constant modulus algorithm (CMA). Schemes based on Stokes space [11][12][13][14][15][16][17][18][19][20][21][22] are not sensitive to carrier phase noise, frequency offset or polarization mixing. However, it is difficult for these schemes to identify high-order modulation formats, which have a large number of clusters.…”

Section: Introductionmentioning

confidence: 99%

Modulation Format Identification Based on Multi-Dimensional Amplitude Features for Elastic Optical Networks

Hao,

He,

Jiang

et al. 2024

Photonics

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A modulation format identification (MFI) scheme based on multi-dimensional amplitude features is proposed for elastic optical networks. According to the multi-dimensional amplitude features, incoming polarization division multiplexed (PDM) signals can be identified as QPSK, 8QAM, 16QAM, 32QAM, 64QAM and 128QAM signals using the k-nearest neighbors (KNNs) algorithm in the digital coherent receivers. The proposed scheme does not require any prior training or optical signal-to-noise ratio (OSNR) information. The performance of the proposed MFI scheme is verified based on numerical simulations with 28GBaud PDM-QPSK/-8QAM/-16QAM/-32QAM/-64QAM/-128QAM signals. The results show that the proposed scheme can achieve 100% of the correct MFI rate for all six modulation formats when the OSNR values are greater than their thresholds corresponding to the 20% forward error correction (FEC) related to a BER of 2.4 × 10−2. Meanwhile, the effects of residual chromatic dispersion, polarization mode dispersion and fiber nonlinearities on the proposed scheme are also explored. Finally, the computational complexity of the proposed scheme is analyzed, which is compared with relevant MFI schemes. The work indicates that the proposed technique could be regarded as a good candidate for identifying modulation formats up to 128QAM.

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Section: Introductionmentioning

confidence: 99%

Modulation Format Identification Based on Multi-Dimensional Amplitude Features for Elastic Optical Networks

Hao,

He,

Jiang

et al. 2024

Photonics

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show abstract

“…The previously-reported MFI schemes for optical fiber communications were roughly classified into the following three categories: (1) data-aided schemes [9][10][11], in which additional pilot information is introduced and the computational complexity of the MFI scheme is low (at the cost of reduced spectral efficiency); (2) schemes based on Stokes space [7,8,[12][13][14][15][16][17][18][19][20][21][22][23], which are not sensitive to carrier phase noise, frequency offset or polarization mixing; (3) schemes based on signal characteristics arising from constant modulus algorithm (CMA) equalization [24][25][26][27][28][29][30][31][32][33], which are based on CMA-equalized signals and do not require any space mapping. Meanwhile, CMA can also compensate for residual chromatic dispersion (CD) and polarization mode dispersion (PMD).…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Modulation Format Identification Based on Amplitude Histogram Distributions for Digital Coherent Receivers

et al. 2023

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In this work, a prior-training-free and low-complexity modulation format identification (MFI) scheme, based on amplitude histogram distributions, was proposed and demonstrated, both numerically and experimentally, for autonomous digital coherent receivers. In the proposed scheme, after having performed power normalization, incoming polarization division multiplexed (PDM) signals were classified into QPSK, 8QAM, 16QAM, 32QAM and 64QAM signals, according to their ratios. Ratios were defined according to specific features of their amplitude histograms. The proposed MFI scheme used only amplitude information. As such, it was insensitive to carrier phase noise. Furthermore, the proposed scheme did not require any prior information, such as optical signal-to-noise ratio (OSNR). The performance of the proposed MFI scheme was numerically verified using 28GBaud PDM-QPSK/-8QAM/-16QAM/-32QAM/-64QAM signals. The numerical simulation results showed that the proposed scheme was able achieve a 100% correct identification rate for all five modulation formats when their OSNR values were higher than the thresholds corresponding to the 20% FEC correcting bit error rate (BER) of 2.4 × 10−2. To further explore the effectiveness of the proposed MFI scheme, proof-of-concept experiments in 28GBaud PDM-QPSK/-8QAM/-16QAM, and 21.5GBaud PDM-32QAM transmission systems were also undertaken, which showed that the proposed scheme as robust against fiber nonlinearities. To explore the scheme’s feasibility for use in practical transmission systems, the computational complexity analysis of the proposed scheme was conducted. It showed that, compared with relevant MFI schemes, the proposed MFI scheme was able to significantly reduce the computational complexity.

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“…Graph-theory can be also used for low complex MF identification [ 21 ]. Finally, MF identifications based on the Stokes space [ 22 , 23 , 24 ] are especially attractive because they can be performed before polarization demultiplexing at the Rx DSP block.…”

Section: Introductionmentioning

confidence: 99%

Accurate Low Complex Modulation Format and Symbol Rate Identification for Autonomous Lightpath Operation

Sequeira

Ruiz

Costa

et al. 2022

Sensors

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Network automation promises to reduce costs while guaranteeing the required performance; this is paramount when dealing with the forecasted highly dynamic traffic that will be generated by new 5G/6G applications. In optical networks, autonomous lightpath operation entails that the optical receiver can identify the configuration of a received optical signal without necessarily being configured from the network controller. This provides relief for the network controller from real-time operation, and it can simplify the operation in multi-domain scenarios, where an optical connection spans across more than one domain. Consequently, in this work, we propose a blind and low complex modulation format (MF) and symbol rate (SR) identification algorithm. The algorithm is based on studying the effects of decoding an optical signal with different MFs and SRs. Extensive MATLAB-based simulations have been carried out which consider a coherent wavelength division multiplexed system based on 32 and 64 quadrature amplitude modulated signals at up to 96 GBd, thus enabling bit rates of up to 800 Gb/s/channel. The results show remarkable identification accuracy in the presence of linear and nonlinear noise for a wide range of feasible configurations.

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Modulation format identification based on phase statistics in Stokes space

Cited by 5 publications

References 15 publications

Modulation Format Identification Based on Multi-Dimensional Amplitude Features for Elastic Optical Networks

Modulation Format Identification Based on Multi-Dimensional Amplitude Features for Elastic Optical Networks

Low-Complexity Modulation Format Identification Based on Amplitude Histogram Distributions for Digital Coherent Receivers

Accurate Low Complex Modulation Format and Symbol Rate Identification for Autonomous Lightpath Operation

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