Hybrid Dy-NFIS & RLS equalization for ZCC code in optical-CDMA over multi-mode optical fiber

For long haul coherent optical fiber communication systems, it is significant to precisely monitor the quality of transmission links and optical signals. The channel capacity beyond Shannon limit of Single-mode optical fiber (SMOF) is achieved with the help of Multi-mode optical fiber (MMOF), where the signal is multiplexed in different spatial modes. To increase single-mode transmission capacity and to avoid a foreseen “capacity crunch”, researchers have been motivated to employ MMOF as an alternative. Furthermore, different multiplexing techniques could be applied in MMOF to improve the communication system. One of these techniques is the Optical Code Division Multiple Access (Optical-CDMA), which simplifies and decentralizes network controls to improve spectral efficiency and information security increasing flexibility in bandwidth granularity. This technique also allows synchronous and simultaneous transmission medium to be shared by many users. However, during the propagation of the data over the MMOF based on Optical-CDMA, an inevitable encountered issue is pulse dispersion, nonlinearity and MAI due to mode coupling. Moreover, pulse dispersion, nonlinearity and MAI are significant aspects for the evaluation of the performance of high-speed MMOF communication systems based on Optical-CDMA. This work suggests a hybrid algorithm based on nonlinear algorithm (Dynamic evolving neural fuzzy inference (Dy-NFIS)) and linear algorithm (Recursive least squares (RLS)) equalization for ZCC code in Optical-CDMA over MMOF. Root mean squared error (RMSE), mean squared error (MSE) and Structural Similarity index (SSIM) are used to measure performance results.

[1]  Faisal Theyab Abed,et al.  Efficient Energy of Smart Grid Education Models for Modern Electric Power System Engineering in Iraq , 2020, IOP Conference Series: Materials Science and Engineering.

[2]  Hussein Seleem,et al.  Efficient interference cancellation detector for asynchronous upstream optical code division multiple access-passive optical network with mixed Poisson-Gaussian noise , 2014, IET Commun..

[3]  Nikola Kasabov,et al.  ECM — A Novel On-line, Evolving Clustering Method and Its Applications , 2001 .

[4]  Faisal Theyab Abed,et al.  Analysis the Efficient Energy Prediction for 5G Wireless Communication Technologies , 2019, Int. J. Emerg. Technol. Learn..

[5]  Nicolae Dumitru Alexandru,et al.  An Approximation of Gaussian Pulses , 2011, PECCS.

[6]  El-Shafie,et al.  Prediction of Suspended Sediment Load Using Data-Driven Models , 2019, Water.

[7]  Hamzeh Beyranvand,et al.  Cellular Underwater Wireless Optical CDMA Network: Potentials and Challenges , 2016, IEEE Access.

[8]  Manoj Kumar,et al.  Design and Performance investigation of multiuser OCDMA network , 2013 .

[9]  Nikola K. Kasabov,et al.  DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction , 2002, IEEE Trans. Fuzzy Syst..

[10]  G. Mahdiraji,et al.  Effects of Fiber Dispersion on the Performance of Optical CDMA Systems , 2012 .

[11]  Qun Song,et al.  Dynamic Neural Fuzzy Inference System , 2008, ICONIP.

[12]  B. Farhang-Boroujeny,et al.  Adaptive Filters: Theory and Applications , 1999 .

[13]  Stephen A. Dyer,et al.  Digital signal processing , 2018, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..

[14]  Changjian Guo,et al.  Impact of ADC Bandwidth and Clipping Ratio on COF-PON Systems Based on Spatial Coding and Subcarrier Multiplexing , 2011, 2011 Symposium on Photonics and Optoelectronics (SOPO).

[15]  Marc Heddebaut,et al.  Theoretical and Experimental Performances Evaluation of a New Multiple Access Technique for Optical Fibers , 2012 .

[16]  Pankaj Sharma,et al.  Link length augmentation of optically coded multi-user network by using Electronic Equalization Technique , 2014, 2014 Recent Advances in Engineering and Computational Sciences (RAECS).

[17]  Mohammed Azmi Al-Betar,et al.  Spam E-mail Filtering using ECOS Algorithms , 2015 .

[18]  Salim Heddam,et al.  Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA , 2014, Environmental Science and Pollution Research.

[19]  Angela Amphawan,et al.  Channel Impulse Response Equalization based on Genetic Algorithm in Mode Division Multiplexing , 2018 .

[20]  Amr Ragheb,et al.  Spectral phase coding based LR-PON , 2015, 2015 11th International Conference on Innovations in Information Technology (IIT).

[21]  Scott C. Douglas,et al.  Numerically-robust O(N/sup 2/) RLS algorithms using least-squares prewhitening , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[22]  Dimitrios Gunopulos,et al.  Incremental support vector machine construction , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[23]  Vishal Sharma,et al.  Pulse Shape Filtering in Wireless Communication-A Critical Analysis , 2011 .

[24]  Hareeta Malani System Identification through RLS Adaptive Filters , 2012 .

[25]  Salim Heddam,et al.  A new approach based on the dynamic evolving neural-fuzzy inference system (DENFIS) for modelling coagulant dosage (Dos): case study of water treatment plant of Algeria , 2015 .

[26]  Zhou Wang,et al.  On the Mathematical Properties of the Structural Similarity Index , 2012, IEEE Transactions on Image Processing.

[27]  Huimin Lu,et al.  A CDMA system implementation with dimming control for visible light communication , 2018 .

[28]  Poompat Saengudomlert,et al.  Transmit power reduction through subcarrier selection for MC-CDMA-based indoor optical wireless communications with IM/DD , 2013, EURASIP J. Wirel. Commun. Netw..

[29]  Soung Chang Liew,et al.  Wireless MIMO Switching: Weighted Sum Mean Square Error and Sum Rate Optimization , 2012, IEEE Transactions on Information Theory.

[30]  M. S Anuar,et al.  LED spectrum slicing for ZCC SAC-OCDMA coding system , 2010, 7th International Symposium on High-capacity Optical Networks and Enabling Technologies.

[31]  R. Attia,et al.  Wavelength and beam launching effects on silica optical fiber in local area networks , 2010 .

[32]  Taufik Abrão,et al.  WDM/OCDM Energy-Efficient Networks Based on Heuristic Ant Colony Optimization , 2016, IEEE Systems Journal.

[33]  J L Wei,et al.  First demonstration of OFDM ECDMA for low cost optical access networks. , 2015, Optics letters.

[34]  Jose Velazquez,et al.  Applications of Adaptive Filtering , 2011 .

[35]  Hichem Mrabet,et al.  Performance enhancement of OCDMA systems for LAN consideration , 2016 .

[36]  Monson H. Hayes,et al.  Statistical Digital Signal Processing and Modeling , 1996 .

[37]  L. Nelson,et al.  Space-division multiplexing in optical fibres , 2013, Nature Photonics.

[38]  Syed Alwee Aljunid,et al.  Development of a Zero Cross-Correlation Code for Spectral-Amplitude Coding Optical Code Division Multiple Access (OCDMA) , 2006 .

[39]  Indu Bala,et al.  Gaussian approximation analysis of ZCC code for multimedia optical CDMA applications , 2009, 2009 11th International Conference on Transparent Optical Networks.

[40]  Haider Th. Salim AL-Rikabi Enhancement of the MIMO-OFDM technologies , 2013 .

[41]  Mohsen Machhout,et al.  Trenched raised cosine FMF for differential mode delay management in next generation optical networks , 2018 .

[42]  Guifang Li,et al.  Space-division multiplexing: the next frontier in optical communication , 2014 .

[43]  Olivier Lopez,et al.  Cascaded optical link on a telecommunication fiber network for ultra-stable frequency dissemination , 2015, Photonics West - Optoelectronic Materials and Devices.

[44]  C. Quek,et al.  Dynamic evolving neural-fuzzy inference system for rainfall-runoff (R-R) modelling , 2011 .

[45]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control , 1994 .

[46]  Jyoti Dhiman,et al.  Comparison between Adaptive filter Algorithms (LMS, NLMS and RLS) , 2013 .

[47]  Upena D. Dalal,et al.  Analysis of second order harmonic distortion due to transmitter non-linearity and chromatic and modal dispersion of optical OFDM SSB modulated signals in SMF-MMF fiber links , 2017 .

[48]  Amin Talei,et al.  Rainfall-runoff Modeling Using Dynamic Evolving Neural Fuzzy Inference System with Online Learning , 2016 .

[49]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[50]  J. Kahn,et al.  Higher-Order Modal Dispersion in Graded-Index Multimode Fiber , 2009, Journal of Lightwave Technology.

[51]  E. Ip,et al.  101.7-Tb/s (370×294-Gb/s) PDM-128QAM-OFDM transmission over 3×55-km SSMF using pilot-based phase noise mitigation , 2011, 2011 Optical Fiber Communication Conference and Exposition and the National Fiber Optic Engineers Conference.

[52]  T. Kailath,et al.  A state-space approach to adaptive RLS filtering , 1994, IEEE Signal Processing Magazine.

[53]  Haider Th. Salim Alrikabi,et al.  Encryption System for Hiding Information Based on Internet of Things , 2021, Int. J. Interact. Mob. Technol..

[54]  Selvakumar Manickam,et al.  Phishing Dynamic Evolving Neural Fuzzy Framework for Online Detection Zero-day Phishing Email , 2013, ArXiv.

[55]  W. Kenneth Jenkins,et al.  Advanced Concepts in Adaptive Signal Processing , 1996 .

[56]  Deepak Nagaria,et al.  LMS Adaptive Filters for Noise Cancellation: A Review , 2017 .

[57]  M. Brandt-Pearce,et al.  Distributed Power Allocation for Multiuser MISO Indoor Visible Light Communications , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[58]  Rihab Salah Khairy,et al.  The Detection of Counterfeit Banknotes Using Ensemble Learning Techniques of AdaBoost and Voting , 2021, International Journal of Intelligent Engineering and Systems.

[59]  M. Eiselt,et al.  Experimental Demonstration of 84 Gb/s PAM-4 Over up to 1.6 km SSMF Using a 20-GHz VCSEL at 1525 nm , 2017, Journal of Lightwave Technology.

[60]  Chi Wan Sung,et al.  Coding for uncoordinated multiple access in visible light positioning systems , 2016, 2016 10th International Conference on Signal Processing and Communication Systems (ICSPCS).

[61]  S. Turitsyn,et al.  Generation of triangular-shaped optical pulses in normally dispersive fibre , 2010 .

[62]  Brij B. Gupta,et al.  ICMPv6 Flood Attack Detection using DENFIS Algorithms , 2013 .

[63]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[64]  Angela Amphawan,et al.  Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexer for optical fiber transmission , 2019, Bulletin of Electrical Engineering and Informatics.

[65]  Nicolae Dumitru Alexandru,et al.  Generation of Quasi-Gaussian Pulses Based on Correlation Techniques , 2012 .

[66]  S. Aljunid,et al.  Design of a New Class of Codes with Zero in Phase Cross Correlation for Spectral Amplitude Coding , 2011 .

[67]  S. Singh,et al.  Nonlinear Effects in Optical Fibers: Origin, Management and Applications , 2007 .

[68]  Nan Chi,et al.  Demonstration of high-speed multi-user multi-carrier CDMA visible light communication , 2015 .

[69]  J. Amudha,et al.  Optimization of Rules in Neuro-Fuzzy Inference Systems , 2018, ICCVBIC 2018.

[70]  Maite Brandt-Pearce,et al.  MIMO signal processing for multiuser VLC systems , 2016, 2016 IEEE Photonics Society Summer Topical Meeting Series (SUM).

[71]  Chih-Ta Yen,et al.  A Study of Dispersion Compensation of Polarization Multiplexing-Based OFDM-OCDMA for Radio-over-Fiber Transmissions , 2016, Sensors.

[72]  Susan P. Worner,et al.  Dynamic Neuro-fuzzy Inference and Statistical Models for Risk Analysis of Pest Insect Establishment , 2004, ICONIP.

[73]  Jeff Hecht,et al.  An Introduction to Fiber Optics , 2015 .

[74]  Hilal A. Fadhil,et al.  Selective mode excitation in SCM-OCDMA , 2013, 2013 IEEE 4th International Conference on Photonics (ICP).

[75]  Ivan Glesk,et al.  Recent advances in all-optical signal processing for performance enhancement of OCDMA interconnects , 2016, 2016 18th International Conference on Transparent Optical Networks (ICTON).

[76]  Jafar Ramadhan Mohammed,et al.  A Study on the Suitability of Genetic Algorithm for Adaptive Channel Equalization , 2012 .

[77]  Mahmoud O. Elish A comparative study of fault density prediction in aspect-oriented systems using MLP, RBF, KNN, RT, DENFIS and SVR models , 2014, Artificial Intelligence Review.

[78]  Nikola K. Kasabov,et al.  Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[79]  Gabriella Piscopo Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Prediction , 2017 .

[80]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[81]  Hilal A. Fadhil,et al.  Comparison of Single Mode Fiber and Multimode Fiber in Deployment of SCM-OCDMA in Local Area Network , 2013 .