Modulation format identification in fiber communications using single dynamical node-based photonic reservoir computing
We present a simple approach based on photonic reservoir computing (P-RC) for modulation format identification (MFI) in optical fiber communications. Here an optically injected semiconductor laser with self-delay feedback is trained with the representative features from the asynchronous amplitude histograms of modulation signals. Numerical simulations are conducted for three widely used modulation formats (on–off keying, differential phase-shift keying, and quadrature amplitude modulation) for various transmission situations where the optical signal-to-noise ratio varies from 12 to 26 dB, the chromatic dispersion varies from
基金项目：National Natural Science Foundation of China
Ya Guo：Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China；School of Electronics and Information, Northwestern Polytechnical University, Xi''an 710072, China
Pu Li：Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China；School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China；Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, China
Adonis Bogris：Department of Informatics and Computer Engineering, University of West Attica, Athens 12243, Greece
K. Alan Shore：School of Electronic Engineering, Bangor University, Wales LL57 1UT, UK
Yamei Zhang：Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Yuncai Wang：School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
备注：National Natural Science Foundation of China
【1】A. Nag, M. Tornatore and B. Mukherjee. Optical network design with mixed line rates and multiple modulation formats. J. Lightwave Technol. 28, 466-475(2010).
【2】S. J. Yoo, A. Lord, M. Jinno and O. Gerstel. Elastic optical networking: a new dawn for the optical layer?. IEEE Commun. Mag. 50, s12-s20(2012).
【3】T. Zhang, J. Wang, Q. Liu, J. Z. Zhou, J. Dai, X. Han, Y. Zhou and K. Xu. Efficient spectrum prediction and inverse design for plasmonic waveguide systems based on artificial neural networks. Photon. Res. 7, 368-380(2019).
【4】Y. Q. Chang, H. Wu, C. Zhao, L. Shen, S. N. Fu and M. Tang. Distributed Brillouin frequency shift extraction via a convolutional neural network. Photon. Res. 8, 690-697(2020).
【5】Z. Pan, C. Yu and A. E. Willner. Optical performance monitoring for the next generation optical communication networks. Opt. Fiber Technol. 16, 20-45(2010).
【6】R. Borkowski, D. Zibar and I. T. Monroy. Anatomy of a digital coherent receiver. IEICE Trans. Commun. E97-B, 1528-1536(2014).
【7】E. E. Azzouz and A. K. Nandi. Automatic Modulation Recognition of Communication Signals. : Kluwer Academic, (1996).
【8】O. A. Dobre, A. Abdi, Y. Bar-Ness and W. Su. A survey of automatic modulation classification techniques: classical approaches and new trends. IET Commun. 1, 137-156(2007).
【9】A. K. Nandi and E. E. Azzouz. Algorithms for automatic modulation recognition of communication signals. IEEE Trans. Commun. 46, 431-436(1998).
【10】C. S. Park, J. H. Choi, S. P. Nah, W. Jang and D. Y. Kim. Automatic modulation recognition of digital signals using wavelet features and SVM. 10th International Conference on Advanced Communication Technology. 387-390(2008).
【11】F. N. Khan, Y. Zhou, A. P. T. Lau and C. Lu. Modulation format identification in heterogeneous fiber-optic networks using artificial neural networks. Opt. Express. 20, 12422-12431(2012).
【12】M. L. D. Wong and A. K. Nandi. Automatic digital modulation recognition using artificial neural network and genetic algorithm. Signal Process. 84, 351-365(2004).
【13】T. J. O’shea, T. Roy and T. C. Clancy. Over the air deep learning based radio signal classification. IEEE J. Sel. Top. Signal Process. 12, 168-179(2018).
【14】D. Wang, M. Zhang, J. Li, Z. Li, J. Li, C. Song and X. Chen. Intelligent constellation diagram analyzer using convolutional neural network-based deep learning. Opt. Express. 25, 17150-17166(2017).
【15】L. Appeltant, M. C. Soriano, G. Van der Sande, J. Danckaert, S. Massar, J. Dambre, B. Schrauwen, C. R. Mirasso and I. Fischer. Information processing using a single dynamical node as complex system. Nat. Commun. 2, (2011).
【16】D. Brunner, M. C. Soriano, C. R. Mirasso and I. Fischer. Parallel photonic information processing at gigabyte per second data rates using transient states. Nat. Commun. 4, (2013).
【17】L. Larger, M. C. Soriano, D. Brunner, L. Appeltant, J. M. Gutierrez, L. Pesquera, C. R. Mirasso and I. Fischer. Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing. Opt. Express. 20, 3241-3249(2012).
【18】R. M. Nguimdo, G. Verschaffelt, J. Danckaert and G. Van der Sande. Fast photonic information processing using semiconductor lasers with delayed optical feedback: role of phase dynamics. Opt. Express. 22, 8672-8686(2014).
【19】L. Larger, A. Baylón-Fuentes, R. Martinenghi, V. S. Udaltsov, Y. K. Chembo and M. Jacquot. High-speed photonic reservoir computing using a time-delay-based architecture: million words per second classification. Phys. Rev. X. 7, (2017).
【20】Y. Paquot, F. Duport, A. Smerieri, J. Dambre, B. Schrauwen, M. Haelterman and S. Massar. Optoelectronic reservoir computing. Sci. Rep. 2, (2012).
【21】R. Martinenghi, S. Rybalko, M. Jacquot, Y. K. Chembo and L. Larger. Photonic nonlinear transient computing with multiple-delay wavelength dynamics. Phys. Rev. Lett. 108, (2012).
【22】F. Duport, B. Schneider, A. Smerieri, M. Haelterman and S. Massar. All-optical reservoir computing. Opt. Express. 20, 22783-22795(2012).
【23】K. Hicke, M. A. Escalona-Morán, D. Brunner, M. C. Soriano, I. Fischer and C. R. Mirasso. Information processing using transient dynamics of semiconductor lasers subject to delayed feedback. IEEE J. Sel. Top. Quantum Electron. 19, (2013).
【24】A. Dejonckheere, F. Duport, A. Smerieri, L. Fang, J. L. Oudar, M. Haelterman and S. Massar. All-optical reservoir computer based on saturation of absorption. Opt. Express. 22, 10868-10881(2014).
【25】R. M. Nguimdo, G. Verschaffelt, J. Danckaert and G. Van der Sande. Simultaneous computation of two independent tasks using reservoir computing based on a single photonic nonlinear node with optical feedback. IEEE Trans. Neural Netw. Learn. Syst. 26, 3301-3307(2015).
【26】Q. Vinckier, F. Duport, A. Smerieri, K. Vandoorne, P. Bienstman, M. Haelterman and S. Massar. High performance photonic reservoir computer based on a coherently driven passive cavity. Optica. 2, 438-446(2015).
【27】J. Bueno, D. Brunner, M. C. Soriano and I. Fischer. Conditions for reservoir computing performance using semiconductor lasers with delayed optical feedback. Opt. Express. 25, 2401-2412(2017).
【28】J. Vatin, D. Rontani and M. Sciamanna. Experimental reservoir computing using VCSEL polarization dynamics. Opt. Express. 27, 18579-18584(2019).
【29】X. Tan, Y. Hou, Z. Wu and G. Xia. Parallel information processing by a reservoir computing system based on a VCSEL subject to double optical feedback and optical injection. Opt. Express. 27, 26070-26079(2019).
【30】Y. Hou, G. Xia, W. Yang, D. Wang, E. Jayaprasath, Z. Jiang, C. Hu and Z. Wu. Prediction performance of reservoir computing system based on a semiconductor laser subject to double optical feedback and optical injection. Opt. Express. 26, 10211-10219(2018).
【31】J. Qin, Q. Zhao, D. Xu, H. Yin, Y. Chang and D. Huang. Optical packet header identification utilizing an all-optical feedback chaotic reservoir computing. Mod. Phys. Lett. B. 30, (2016).
【32】J. Qin, Q. Zhao, H. Yin, Y. Jin and C. Liu. Numerical simulation and experiment on optical packet header recognition utilizing reservoir computing based on optoelectronic feedback. IEEE Photon. J. 9, (2017).
【33】A. Argyris, J. Bueno and I. Fischer. Photonic machine learning implementation for signal recovery in optical communications. Sci. Rep. 8, (2018).
【34】A. Argyris, J. Bueno and I. Fischer. PAM-4 transmission at 1550 nm using photonic reservoir computing post-processing. IEEE Access. 7, 37017-37025(2019).
【35】H. JaegerH. Jaeger. Short term memory in echo state networks. GMD Rep. 152, (2002).
【36】A. Wang, Y. Wang and H. He. Enhancing the bandwidth of the optical chaotic signal generated by a semiconductor laser with optical feedback. IEEE Photon. Technol. Lett. 20, 1633-1635(2008).
【37】A. Wang, Y. Wang and J. Wang. Route to broadband chaos in a chaotic laser diode subject to optical injection. Opt. Lett. 34, 1144-1146(2009).
【38】L. Appeltant, G. Van der Sande, J. Danckaert and I. Fischer. Constructing optimized binary masks for reservoir computing with delay systems. Sci. Rep. 4, (2015).
【39】M. C. Soriano, S. Ortín, D. Brunner, L. Larger, C. R. Mirasso, I. Fischer and L. Pesquera. Optoelectronic reservoir computing: tackling noise-induced performance degradation. Opt. Express. 21, 12-20(2013).
【40】J. Nakayama, K. Kanno and A. Uchida. Laser dynamical reservoir computing with consistency: an approach of a chaos mask signal. Opt. Express. 24, 8679-8692(2016).
【41】R. Lang and K. Kobayashi. External optical feedback effects on semiconductor injection laser properties. IEEE J. Quantum Electron. 16, 347-355(1980).
【42】S. Okada, M. Ohzeki and S. Taguchi. Efficient partition of integer optimization problems with one-hot encoding. Sci. Rep. 9, (2019).
【43】Q. Xiang, Y. Yang, Q. Zhang and Y. Yao. Joint and accurate OSNR estimation and modulation format identification scheme using the feature-based ANN. IEEE Photon. J. 11, (2019).
【44】Y. Bengio and Y. Grandvalet. No unbiased estimator of the variance of K-fold cross-validation. J. Mach. Learn. Res. 5, 1089-1105(2004).
【45】P. Li, Q. Cai, J. Zhang, B. Xu, Y. Liu, A. Bogirs, K. A. Shore and Y. Wang. Observation of flat chaos generation using an optical feedback multi-mode laser with a band-pass filter. Opt. Express. 27, 17859-17867(2019).
【46】A. Zhao, N. Jiang, C. Xue, J. Tang and K. Qiu. Wideband complex- enhanced chaos generation using a semiconductor laser subject to delay-interfered self-phase-modulated feedback. Opt. Express. 27, 12336-12348(2019).
【47】B. G. MobasseriB. G. Mobasseri. Digital modulation classification using constellation shape. Signal Process. 80, 251-277(2000).
【48】L. Guesmi, A. M. Ragheb, H. Fathallah and M. Menif. Experimental demonstration of simultaneous modulation format/symbol rate identification and optical performance monitoring for coherent optical systems. J. Lightwave Technol. 36, 2230-2239(2017).
【49】W. S. Saif, A. M. Ragheb, H. E. Seleem, T. A. Alshawi and S. A. Alshebeili. Modulation format identification in mode division multiplexed optical networks. IEEE Access. 7, (2019).
【50】I. Park, I. Fischer and W. Els??er. Highly nondegenerate four-wave mixing in a tunable dual-mode semiconductor laser. Appl. Phys. Lett. 84, 5189-5191(2004).
Qiang Cai, Ya Guo, Pu Li, Adonis Bogris, K. Alan Shore, Yamei Zhang, and Yuncai Wang, "Modulation format identification in fiber communications using single dynamical node-based photonic reservoir computing," Photonics Research 9(1), B1 (2021)