Available online at www.sciencedirect.com Available online at www.sciencedirect.com
Available
online at www.sciencedirect.com Procedia Computer Science 00 (2018) 000–000 Procedia Computer Science 00 (2018) 000–000
ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Procedia Computer Science 134 (2018) 196–203
The 13th International Conference on Future Networks and Communications The 13th International Conference on 2018) Future Networks and Communications (FNC (FNC 2018)
Simulation Platform of Optical Transmission System in Matlab Simulation Platform of Optical Transmission System in Matlab Simulink Simulink Pavol Šalík*, Rastislav Róka, Tomáš Gorazd Pavol Šalík*, Rastislav Róka, Tomáš Gorazd
Slovak University of Technology, Faculty of Electrical Engineering and Information Technologies Institute of Multimedia Information and Communication Slovak University of Technology, Faculty of Electrical Engineering andTechnologies Information Technologies Ilkovičova 3, 812 19 Bratislava, Slovakia Technologies Institute of Multimedia Information and Communication Ilkovičova 3, 812 19 Bratislava, Slovakia
Abstract Abstract This paper deals with simulation platform of optical transmission system in Matlab Simulink. A detailed mathematical This paper deals withto simulation platform Matlab Simulink. A detailed mathematical methodology in order accurately model partsofofoptical optical transmission transmission system isinpresented. The simulation platform is suitable methodology order channel to accurately model parts of optical is presented. simulation is suitable for simulationinsingle optical transmission system.transmission The selectedsystem approach takes intoThe account noisesplatform that occurs on the for simulation channelsystem. optical transmission system. The selected approach takes into account noises that occurs on the parts of optical single transmission parts of optical transmission system. © 2018 2018 The Ltd. © The Authors. Authors.Published PublishedbybyElsevier Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Peer-review under responsibility of the scientific committee of the 13th International Conference on Future Networks and This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Communications, FNC-2018 and the 15th International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2018. Keywords: Simulation, Simulink, Optical transmission system, DFB laser, Mach-Zender Modulator Keywords: Simulation, Simulink, Optical transmission system, DFB laser, Mach-Zender Modulator
1. Introduction 1. Introduction Ultra capacity and high speed optical communications have become essential techniques for backbone -1 Ultra capacity and Due high tospeed optical communications become speed essential techniques for channel) backbone transmission networks. increased demands for the data have transmission (100Gb⋅s per one is -1 transmission networks. to increased demands for the data (100Gb⋅s per oneto channel) is very important to avoidDue expensive practical demonstration and transmission testing [1,2]. speed Therefore, is important search for very important to avoid expensive practical demonstration andbehaviour testing [1,2]. Therefore, is important search for modelling platform which will be able to accurately describe of different parts of optical to transmission modelling platform which will be able to accurately describe of different of optical transmission under different working conditions and their limitations. Such abehaviour system must be basedparts on measurement parameters under different working conditions and their limitations. Such a systemare must be expensive based on measurement in order to predict its performance. Commercial simulation softwares often and not easilyparameters adaptive. in order predict its based performance. Commercial simulation are often expensive not easily adaptive. Many of to them are not on measurements parameters andsoftwares the data extraction for further and processing is difficult if Many of them are not based on measurements parameters and the data extraction for further processing is difficult if even possible. even possible. * Corresponding author. Tel.: +421918390804; * E-mail Corresponding author. Tel.: +421918390804; address:
[email protected]
E-mail address:
[email protected]
1877-0509 © 2018 The Authors. Published by Elsevier Ltd. This is an open access under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). 1877-0509 © 2018 Thearticle Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). 1877-0509 © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 13th International Conference on Future Networks and Communications, FNC-2018 and the 15th International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2018. 10.1016/j.procs.2018.07.162
2
Pavol Šalík et al. / Procedia Computer Science 134 (2018) 196–203 Pavol Salik/ Procedia Computer Science 00 (2015) 000–000
197
Therefore, we have decided to create our own simulation platform based on Matlab Simulink, which has become the universal modelling tool in most universities and research laboratories around the world. In this paper there is optical simulation platform presented. This optical simulation platform is extension of our previous work [3,4,5]. The optical simulation platform consists of models of optical components listed bellow
Bernoulli data generator Continues wave Distributed feedback laser (CW-DFB) Mach – Zender interferometric modulator Optical transmission fiber Mach – Zender interferometric demodulator
The document is organized as follows. The theoretical background for separate optical components listed above is described in the next section. The third section contains description of the simulation platform and simulation results. Finally, there is representation of results and conclusion of our work. 2. Modelling approach 2.1. DFB Laser The dynamic properties of laser can be modelled via coupled rate equations listed in (1) – (3). These equations describe inner interactions between electron number N(t), photon number S(t) and optical phase of photons Φ(t). This approach takes into account fluctuations of parameters described below and using the coupled rate equations is possible to create efficient numerical model of DFB laser source [6].
N (t) N 0 dN (t ) I (t) N (t) g S (t ) FN (t ) dt q 1 S (t) n
N (t) N0 dS (t ) S (t) N (t) g FS (t ) S (t ) p n dt 1 S (t) d (t ) g N (t) N avg F (t ) dt 2
(1)
(2)
(3)
Where g is gain slope constant coefficient, N0 is carrier denisty at transparency, ε is gain compression factor, τp is the photon lifetime, β is the sponataneous emission coupled into lasing mode, I(t) is the injection current, q is the electron charge, τn is the electron lifetime, α is the linewidth enchancement factor, Navg is the time averaged carrier number. For simulation purposes is it necessary to take into account noise parameters which are representing intensity phase and frequency fluctuations. These fluctuations are caused by the spontaneous emission, electron hole recombination, and can be assumed to be langevin noise sources Fi(t), where i can be substituted with S,n or θ depending on the equation in which it is used. More about noise source modelling for DFB laser can be found in [7], [8],[9]. Numerical results of output parameters of the DFB laser, were obtained using fourth-order Runge-Kutta algorithm using a short interval of Δt = 10 ps. The rate equations in the laser model are presented in a form containing only parameters that were extracted from measurements. More about extraction process and parameters used in this simulation can be found in [6]. Time variations of output laser characteristics for the steady-state mode of the DFB laser (continues wave lasing mode). (N(t), S(t), θ(t)) can be seen in Fig.1.
198
Author Computer ScienceScience 00 (2015) Pavolname Šalík/ Procedia et al. / Procedia Computer 134000–000 (2018) 196–203
3
Fig. 1. Time variations of steady-state of (a) electron number; (b) photon number; (c) lasing frequency fluctuation In these equations, nonlinear and diffusion effects are lumped together as field-dependent optical gain compression. The term 1/(1+εS(t)) used in (1), (2) is the best option for numerical solution of the DFB lasers with high photon density, according to [10]. The simulation platform is focused on external modulation, therefore the optical feedback, which represents the light reflection on connector connected to optical fiber, can be neglected. If one wants to consider light reflections, the equations (1) - (3) will be no longer suitable. For accurate results, it is important to keep the condition that bias current have to be greater the threshold current. These measurements are simulated for I=12.9 mA. Threshold current is according to [6] Ith= 9.93 mA.
Fig. 2. (a) output power fluctuation; (b) phase fluctuation; (c) power spectrum Output power fluctuation, fluctuation of phase and output power spectrum is displayed in Fig. 2. Central lasing frequency is set to 1550 nm which is equals to 193.1 THz in frequency domain. According to [11] is better to use transmitted light in form of complex envelope in baseband than the high frequency signal, if it meets the condition that frequency of optical signal is much larger that the spectral bandwidth of optical signal. The frequency used for purpose of optical transmission is too high to fulfil sampling theorem, therefore is need of adjustment of optical carrier2.2. Mach-Zender interferometric modulator Mach-Zender interferometric modulator (MZIM) is optical intensity modulator, which operates on principle of interference of optical field of two lightwave components. The input waveguide structure splits input lightwave in two arms. The attenuation in each waveguide is normally 3dB. Each arm of the modulator contains LiNbO3 crystal which employs a phase modulation due to driving current. The lightwaves from two arms are coupled at the output of the MZIM. For simulation platform a single drive MZIM is used, which means there is only single RF voltage driving on arms of modulator.
4
Pavol Šalík et al. / Procedia Computer Science 134 (2018) 196–203 Pavol Salik/ Procedia Computer Science 00 (2015) 000–000
199
Transmitted optical filed E(t) can be written as:
E0
EiRMS jct j1 (t ) e j2 (t ) e e 2
(4)
Where ωc is the carrier frequency, E(t) is transmitted optical field EiRMS is the root mean square value of the carrier and θ1(t), θ2(t) are the temporal phase changes in LiNBO3. In the Fig. 5 can be seen function of MZIM in Simulink simulation platform.
Fig. 3. Simulink MZIM demonstration Fig. 3 describes Simulink model of MZIM. Data stream is shaped as a Gaussian pulse. In arm 1 driving voltage causes phase shift π when logical 0 occurs. Second arm of the MZIM is without phase shift. Finally, two arms are coupled together and produces output modulated signal. Signal from DFB is interpreted as a complex envelope. Phase chirps are caused by single drive constellation and can be removed by push-pull constellation of MZIM. 2.3. Optical receiver The photodetector is a key element of optical receiver situated on the end of the optical transmission system. For the optical receiver is most used PIN diode (PIN) and Avalanche Photodiode (APD). In our Simulink platform the model of PIN diode is used. Important parameters of the receiver are the input signal power and sum of noise sources at the receiver [13]. The received optical signal is influenced by different sources of receiver noises including: quantum shot noise yield as:
iS
1
PD
2qI p B
(5)
Pavol Šalík et al. / Procedia Computer Science 134 (2018) 196–203 Author name / Procedia Computer Science 00 (2015) 000–000
200
5
Thermal (Johnson) noise is given by:
1
iT
PD
2 k BTRB
(6)
Dark noise can be written as:
iQ
1
PD
2qI dc B
(7)
Where q is the electron charge, Ip is the photocurrent, B is the electrical signal of the bandwidth attenuated by 3dB, kbis the Boltzmann constant, T is the absolute temperature and R is the load resistance, ηPD is the quantum efficiency of a photo diode and idc the dark current. The receiver generates electrons which are amplified through implemented a gain [13][14]. 2.4. EDFA amplifier EDFA amplifier can be constructed in Simulink as embed Matlab function. This function is able to calculate the EDFA gain based on the amplitude of the received signal, the pumping power, operating wavelength and the length of used erbium fiber. Noise source of EDFA can be assumed to be Gausian random process with zero mean value. EDFA gain apllied to input signal can be shown in (8)
PSout
P W1 2 s 1 2 ase W1 3 s 1 2 2 1 hcA PSin e N s 1 2 L 1 A W1 2 W2 1 s 1 2 2 1 P ASE W13 hcA
(8)
where Γs is the overlap factor, λ is the signal wavelength, σ1-2 is the absorption factor due to signal σ2-1 is the emission factor due to, σ1-3 is absorption factor due to pump signal, σ3-1 is emission factor due to pump signal, W transition rates between the energy states, τ is the electron lift time, h je Planck constant, PASE is the noise power, L is the length of the erbium doped fiber, c speed of the light, A is the core area of EDF and Psin is the power of input signal. List of extracted paramters for simulating EDFA can be found in [15] 3. Simulation platform in Matlab Simulink R2017b The whole simulation platform is performed in Matlab R2017b Simulink software. In Fig. 4 there is displayed model of optical transmission system including following parts. Bernoulli generator (green) represents data stream
Fig. 4. Schematics of simulation platform of optical transmission system
6
Pavol Salik/ Procedia Computer Science 00 (2015) 000–000 Pavol Šalík et al. / Procedia Computer Science 134 (2018) 196–203
201
which leads to the block of MZIM. Bernoulli generator data are shaped as Gaussian wave, to maintain shape of real generated data. DFB laser block contains model of DFB laser in continues mode wave lasing, on which is modulated our information data from data stream. Central lasing wavelength is λ=1550 nm. SMF represents model of single mode optical fiber. In this modulation is used fiber with these parameters: length l=80km, polarization mode dispersion (PMD=10 ps/nm.km), chromatic dispersion (CD=10 ps/nnm.km), total attenuation ( atotal = 16,8 dB). Block eye diagram and constellation are used to evaluate transmitted signal, and estimate bit error rate of that signal. The optical signal is transferred using On – Off keying modulation format with data speed 10Gbs-1. In Fig.5 can be found internal mechanics of MZIM and its phase shifter used in upper arm. First the lightwave must be attenuated by 3dB to simulate splitter at the input of MZIM. Then is light processed in two separate arms of MZIM. Lightwave in lower arm remain unchanged, while lightwave in upper arm have a phase change according to data stream. Phase sifter works as follows. Randomly generated Gaussian pulses from data stream are multiplied by π. This converts data stream to a range of radian values (π for logical “1” and zero for logical ”0”). The MZIM generates phase shift of 180 degrees only if a zero is required at modulator output. This causes that for logical “1” is zero-degree phase shift generated (-π+ π=0) and for logical “0” is 180-degree phase shift generated (0+ π= π)
Fig. 5. a) Schematics of the MZIM b) schematics of the phase shifter Model of optical fiber is constructed on the basis of addition of negative effects to transmitted light, included in real optical fiber. In Fig. 6 can be seen schematics of model of optical transmission fiber where each block represents one negative effect in real optical fiber. This model of optical transmission fiber was part of our previous work. Detailed description of this model can be found in [3].
Fig. 6. Schematics of the optical transmission fiber In Fig. 7 there is optical receiver displayed. We use only one channel transmission in presented model, hence no filters are needed in optical receiver model. First, the optical signal is amplified by the EDFA amplifier. ENoise source representing the EFA noise is added to the amplified signal. Further, the signal is sent to the photodiode that provides the conversion from an optical signal to an electrical signal. The noise sources associated with the photodiode are added to the signal. Then is the signal sent into measurements blocks in order to estimate Q factor and the bit error rate.
Pavol Šalík et al. / Procedia Computer Science 134 (2018) 196–203 Author name / Procedia Computer Science 00 (2015) 000–000
202
7
Fig. 7. Schematics of the optical receiver Eye diagram of transmitted OOK pulse can be seen in the Fig. 10. An eye diagram is a common indicator of the quality of signals in high-speed digital transmissions. Bit error rate can be estimated using many methods (MonteCarlo, MGD method, GPD method, …). Bit error rate can be computed using Q factor, which can be extracted from eye diagram as follows:
Q
I1 I 0 1 0
(9)
Fig. 8. Eye diagram of transmitted OOK pulse after 80km In this simulation Q= 19.13 which yields BER= 7.1037e-82. In optical communications we can consider BER bellow 1 x 10-12 as error free communication since that means that only one bit of 1 000 000 000 000 is incorrectly received.
8
Pavol Šalík et al. / Procedia Computer Science 134 (2018) 196–203 Pavol Salik/ Procedia Computer Science 00 (2015) 000–000
203
4. Conclusion A complex simulation for optical transmission system created in Matlab Simulink R2017b has been presented. Simulations are based on detailed mathematical methodology presented in this article. This paper is part of dissertation thesis dedicated to creation of simulation platform simulation platform of optical transmission system in Matlab Simulink The main benefit of this simulation software is that the optics models are based on equations that contain parameters extracted by measuring from real devices. The possibility of additional data storage and processing is more flexible than in commercial softwares. The presented simulation platform has showed fundamental characteristics properties which are important to implement it in further numerical simulation platform. 5. Acknowledgement This work is a part of research activities conducted at Slovak University of Technology Bratislava, Faculty of Electrical Engineering and Information Technology, Institute of Multimedia Information and Communication Technologies, within the scope of projects VEGA agency project - 1/0462/17 “Modelling of qualitative parameters in IMS networks”, and KEGA No. 007STU-4/2016 “Progressive educational methods in the field of telecommunications multiservice networks”. References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18]
Cisco 2015 ‘The zettabyte era: Trends and analysis’, white paper http://cisco.com/c/en/us/solutions/collateral/service-provider/visualnetworking-index-vni/VNI_Hyperconnectivity_WP.html Xin M., Meiuha B., Yan F., Longheng L., Weisheng H. (2017) ‘Experimental study of NRZ, Duobinary, PAM-4 in O-Band DMLBased 100G-EPON ’ IEEE Photonics Technology Letters, vol. 29, no.17 Róka R. and Čertík F. (2015) ‘Simulation tools for broadband passive optical networks,’ Simulation Technologies in Networking and Communications: Selecting the Best Tool for the Test. CRC Press, Taylor and Francis Group, pp. 337-364 Šalík P. and Róka R. (2017) ‘Impact of environmental influences on multilevel modulation formats at the signal transmission in the optical transmission medium’ Journal IJCNIS, vol.9, pp.76-87, ISSN 2076-0930 Šalík P., Čertík F., Róka R. (2015) ‘Duobinary modulation format in optical communication systems’ Advances in Signal Processing vol.3, no.1, pp.1-7, ISSN 2332-6883 Fatadin I., Ives D., Wicks, M. (2006) ‘Numerical simulation of intensity and phase noise from extracted parameters for CW DFB lasers’ IEEE J Quant. Electr., vol.42, no.9, pp.934–941 Šalík P. and Róka R. (2017) ‘Analysis of Possibilities for Numerical Simulations of Continues Wave DFB Laser’ ICUMT 2017 - 9th International Congress, Munich (Germany), pp. 215-219, ISBN 978-1-5386-3434-9 Ahmed M., Yamada M., Saito M. (2001) ‘Numerical modelig of intensity and phase noise in semiconductor lasers’ IEEE J. Quantum Electron., vol.37 Gao J., Li X., Flucke J., Boeck, G. (2004) ‘Direct parameter-extraction method for laser diode rate-equation model‘ J. Lightwave Technology, vol.22, pp. 1604-1609 Tomita A., Suzuki, A. (1991) ‘A new density matrix theory for semiconductor lasers, including non- Markovain intraband relaxation and its application to nolinear gain ‘IEEE J. Quantum Electron., vol.27, no. 6, pp. 1630-1641 Proakis J., Salehi M. (2008) 'Digital communications,‘ 5th ed., New York:McGraw-Hill, pp. 74-159 Krahenbuhl R., Cole J.H., Moeller R.P., Howerton M.M. (2009) ‘High-speed optical modulator in LiNbO3 with cascaded resonanttype electrodes‘ Journal of Lightwave Technology, 24(5), 2184–2189 Gateva S. 'Photodetectors', Croatia, InTech, pp. 22-24, March 2012, ISBN 9789535103585 Ghassemlooy Z., Popoola W., Rajbhandari S. (2008) 'Optical Wireless Communications System and Channel Modelling with MATLAB®', CRCPress, pp. 57-74, ISBN 9781439852354 Binh L.I. (2014) 'Optical Fiber communication system with MATLAB® and Simulink models', CRC Press, pp. 355-401, June 2014, ISBN 978-1-4822-1752-0 Róka R. and Čertík F. (2015) ‘Simulation and analysis of the signal transmission in the optical transmission medium’ SIMULTECH 2015 – 5th Int. Conf. on Simulation and Modeling Methodologies, Technologies and Applications, Colmar ( France ), pp. 219-226 Róka R. (2015) ’The environment of fixed transmission media and their negative influences in the simulation’ Int. Journal of Mathematics and Computers in Simulation IJMCS, vol.9, pp. 190-205, ISSN 1998-0159 Róka R., Mokráň M., Šalík, P. (2017) ‘Simulation of negative influences on the CWDM signal transmission in the optical transmission media’, Int. Journal of Circuits, Systems and Signal Processing IJCSSP, vol.11, pp. 75-80, Online ISSN 1998-4464
