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Silicon-Germanium Dioxide and Aluminum Indium Gallium Arsenide-Based Acoustic Optic Modulators

  • Hazem M. El-Hageen , Aadel M. Alatwi and Ahmed Nabih Zaki Rashed EMAIL logo
Published/Copyright: June 10, 2020
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Abstract

The purpose of this study was to clarify the silicon-germanium dioxide (SiGeO2) and Aluminum Indium Gallium Arsenide (AlInGaAs) based acoustic optic modulators for upgrading transmission performance characteristics. The transient time response of these modulators is analyzed and discussed in detail. The 3-dB modulation signal bandwidth, diffraction signal efficiency, signal rise time, and signal quality factor with minimum data error rates are also considered. The proposed models with silicon-germanium dioxide and Aluminum Indium Gallium Arsenide acoustic optic modulators were compared to the previous model with silicon acoustic optic modulators. The results confirmed the high-performance efficiency of the proposed models when compared to the previous model, in both the lowest transient time response and the highest acoustic optic modulators speed response.

1 Introduction

Acoustic, optical devices are used in optical systems for light beam control and signal processing applications [1, 2, 3, 4]. Acoustic optics has developed into a mature technology and is deployed in a wide range of optical system applications [5, 6, 7, 8, 9]. They are used in optical information processing, tunable optical filters, deflectors, broadband delay lines, mode-lockers, acoustic optic sensors, and laser radiation modulators [10, 11, 12, 13]. An acousto-optic modulator (AOM), also called a Bragg cell, uses sound waves to diffract the frequency of light. As with a permanent Bragg grating, the various wavelengths are spatially diffracted and separated from each other. When ultrasonic waves propagate on optical fibers, it causes periodic micro-bending of the optical fibers and a change in the refraction index of the fiber core. This bending is called the elastic-optic or acousto-optic effect. Although this basic theory of acousto-optic diffraction in isotropic media was well understood, there were relatively few practical applications before the invention of the laser [14, 15, 16, 17, 18]. It was the need for optical devices for laser beam control that stimulated extensive research on the theory and practice of acoustooptics. Over the years, the acousto-optic effect has been exploited for the development of dynamic and reconfigurable all-fiber devices. The use of flexural, longitudinal, or torsional elastic modes led to the development of tunable filters, frequency shifters, and switches [19]. Recently, the acousto-optic effect has also been used as a technique for the fine characterization of optical fibers [20, 21, 22], and the generation of cylindrical vector beams [23, 24]. In recent years, the development of superior acousto-optic materials and efficient broadband transducers are the primary contributors to significant progress in acousto-optic (AO) devices [25, 26].

Modulating an incoming laser light can be achieved with an AOM by varying the amplitude and frequency of acoustic waves traveling through the crystal [27]. Many characteristics, such as laser beam deflection, intensity modulation, phase modulation, and frequency shifting, can all be achieved using the AOM [27]. To describe this acousto-optic effect in crystals, a plane wave analysis can be used to determine the frequency and angular characteristics of the acousto-optic interaction [28, 29, 30, 31]. In this approach, the acoustic wave is approximated as a single plane wave typically propagating to the transducer [17, 18, 32, 33, 34, 35]. The frequency or angular dependence is obtained fromthe phase mismatch caused by the change of acoustic frequency or incident optical wave direction [36, 37, 38, 39, 40, 41, 42, 43].

2 Acoustic Optic Modulators Description with Equations Analysis

Figure 1 shows a basic schematic view of the acoustic optic modulators. The incident optical beam is assumed to be a plane wave propagating near the z-axis in the xz plane (referred to as the interaction plane).

Figure 1 View of the acoustic optic modulators.
Figure 1

View of the acoustic optic modulators.

To accommodate the finite size of the transducer, the acoustic beam is modeled as an angular spectrum of plane waves propagating near the x-axis. The AO diffraction only occurs in the interaction plane where the phase-matching condition is satisfied. The intensity and distribution of the diffracted light are proportional to the acoustic power spectra. The angle of diffraction is a function of the acoustic frequency, and acoustic velocity of the optical device is [14, 17, 18]:

(1)θ=λfaVa,

θ is the incident beam laser and the diffracted laser beam. The diffraction efficiency is [14, 17, 28, 37, 38]:

(2)η=πλM2PaW2H,

Where Pa is the acousto power, M2 is the figure of merit for the acoustic optic material, W is the modulator width, H is the modulator length or height. The light beam waist diameter is expressed by [5, 14, 17, 29, 39]:

(3)d=1.27FλD,

Where F is the length of the focal lens, D is the beam diameter of the laser, and (τr) is the acoustic optic modulator rise time [5, 14, 17, 40]:

(4)τr=0.66dVa,

The 3-dB frequency bandwidth is a function of the acoustic optic modulator rise time [5, 6, 14, 17, 30, 31, 41]:

(5)f3dB=12τr,

The signal modulation frequency of the acoustic optic modulators can be utilized as [5, 6, 14, 17, 32, 42]:

(6)fm=0.29ατr,

Where α is the signal loss through the acoustic optic modulators. The modulator transfer function of the acoustic optic modulators can be modeled as the following [5, 6, 17, 33, 43]:

(7)MTF=exp(0.833fcfm)2,

Where the SiGeO2 acoustic optic modulator’s acoustic velocity value is 4.2×106 mm/sec, its loss value is 0.063 dB/GHz.mm, and its figure of merit value is 34.5×10−15 m2/W. While the AlInGaAs acoustic optic modulators velocity value is 6.32×106 mm/sec, its loss value is 0.038 dB/GHz.mm, and its figure of merit value is 44.8×10−15 m2/W. The contrast ratio is a function of both the transfer function and signal modulation frequency and is shown as [6, 14, 17, 34, 35]:

(8)CRfm=1+MTFfm1MTFfm,
(9)CRdB=10logCRfm

Where the materials-based acoustic optic modulators can be expressed as the refractive index [6, 14, 17, 35]:

(10)n=B1+B2λ2λ2B32

Where the constants for the proposed SiGeO2 and AlIn-GaAs AOMs are clarified based on Refs. [6, 7, 14, 17]. Where B1 = 0.6542, B2 = 6.654 (T/T0), B3 = 7.8765 for SiGeO2AOM, B1 = 1.6543,B2 = 0.2136 (T/T0), and B3 = 3.6532 for AlInGaAs AOM [6, 7, 14, 17]. The acoustic optic modulator Q-factor and its bit error rates are expressed as [5, 6, 14, 17]:

(11)Q=2πλLnVa

The higher the modulation speed, the smaller the transit time that can be achieved. So, the transient AOM time and the modulation speed are expressed as [14, 17, 36, 43]:

(12)Tt=dVa,
(13)MS=0.25Tt

3 Simulation Results and Discussions

The selection of AO materials depends on the specific device application. AlInGaAs is perhaps the best choice for making wideband AO modulators. High optical transparency over the wavelength range of interest is achievable in large single crystals properties that are specifically required for AO device applications. The transient time, modulator Q-factor, modulation contrast ratio, 3-dB frequency bandwidth, modulation frequency, and modulator performance are dependent on the variables defined in Table 1.

Table 1

Variables for the acoustic optic modulators

VariablesVariable DefinitionValues/units
T = T0Ambient temperature300 K-450 K
𝛬Laser wavelength1550 nm
faAcoustic frequency5 KHz
FModulator focal length10 mm
Ddiameter of laser beam0.1 mm-0.5 mm
PaAcoustic power100 mW
HHeight of modulatorH = 10 mm
LLength of interaction0.35 mm
WWidth of the modulator8 mm

Figure 2 illustrates the variations in modulator rise time related to laser beam diameter for both previous and proposed AOMs at room temperature. The modulator rise time for AlInGaAs AOM is 12 ns with a 0.1 mm beam diameter, 9 ns with a 0.3 mm beam diameter, and 6 ns with a 0.5 mm beam diameter. The modulator rise time for SiGeO2 AOM is 15 ns with a 0.1 mm beam diameter, 10.5 ns with a 0.3 mm diameter beam, and 6.565 ns with a 0.5 mm diameter beam. For the previous silicon AOM, the modulator rise time is 20 ns with a 0.1mmbeam diameter, 14 ns with a 0.3 mm beam diameter, and 8 ns with a 0.5 mm beam diameter.

Figure 2 Variations in modulator rise time in relation to laser beam diameter for the previous and the proposed AOMs at room temperature
Figure 2

Variations in modulator rise time in relation to laser beam diameter for the previous and the proposed AOMs at room temperature

Figure 3 shows the variations in modulator frequency response related to beam diameter for both the previous and proposed AOMs at room temperature. The modulator frequency response for AlInGaAs AOM is 3 GHz with a 0.1 mm beam diameter, 9.81 GHz with a 0.3 mm beam diameter, and 36 GHz with a 0.5 mm beam diameter. The modulator frequency response for SiGeO2 AOM is 2 GHz with a beam diameter of 0.1 mm, 8 GHz with a 0.3 mm beam diameter, and 32 GHz with a 0.5 mm beam diameter. The modulator frequency response for the previous silicon AOM is 1.5 GHz with a 0.1 mm beam diameter, 6 GHz with a 0.3 mm beam diameter, and 24 GHz with a 0.5 mm beam diameter.

Figure 3 Variations in modulator frequency response in relation to laser beam diameter for the previous and the proposed AOMs at room temperature
Figure 3

Variations in modulator frequency response in relation to laser beam diameter for the previous and the proposed AOMs at room temperature

Figure 4 shows the variations in modulation frequency in relation to the laser beam diameter for both the previous and proposed AOMs at room temperature. The modulation frequency for AlInGaAs AOM is 6 GHz with a 0.1 mm beam diameter, 24 GHz with a 0.3 mm beam diameter, and 96 GHz with a 0.5 mm beam diameter. The modulation frequency for SiGeO2 AOM is 5 GHz with a 0.1 mm beam diameter, 20 GHz with a 0.3 mm beam diameter, and 80 GHz with a 0.5 mm beam diameter. The modulation frequency for the previous silicon AOM is 4 GHz with a 0.1 mm beam diameter, 16 GHz with a 0.3 mm beam diameter, and 64 GHz with a 0.5 mm beam diameter.

Figure 4 Variations in modulation frequency in relation to laser beam diameter for the previous and proposed AOMs at room temperature
Figure 4

Variations in modulation frequency in relation to laser beam diameter for the previous and proposed AOMs at room temperature

Figure 5 shows the variations in modulator speed response in relation to the laser beam diameter for both the previous and proposed AOMs at room temperature. The modulator speed response for AlInGaAs AOM is 6.5 GHz with a 0.1 mm beam diameter, 25 GHz with a 0.3 mm beam diameter, and 97 GHz with a 0.5 mm beam diameter. The modulator speed response for SiGeO2 AOM is 5.5 GHz with a 0.1 mm beam diameter, 21 GHz with a 0.3 mm beam diameter, and 82 GHz with a 0.5 mm beam diameter. The modulator speed response for the previous silicon AOM is 4.5 GHz with a 0.1 mm beam diameter, 18 GHz with a 0.3 mm beam diameter, and 66 GHz with a 0.5 mm beam diameter.

Figure 5 Variations in modulator speed response in relation to laser beam diameter for the previous and proposed AOMs at room temperature
Figure 5

Variations in modulator speed response in relation to laser beam diameter for the previous and proposed AOMs at room temperature

Figure 6 shows the variations in modulator transient time response in relation to the laser beam diameter for the previous and proposed AOMs at room temperature. The modulator transient time response for AlInGaAs AOM is 320 ns with a 0.1 mm beam diameter, 200 ns with a 0.3 mm beam diameter, and 75 ns with a 0.5 mm beam diameter. The modulator transient time response for SiGeO2 AOM is 350 ns with a 0.1 mm beam diameter, 250 ns with a 0.3 mm beam diameter, and 120 ns with a 0.5 mm beam diameter. The modulator transient time response for the previous silicon AOM is 480 ns with a 0.1 mm beam diameter, 400 ns with 0.3 mm beam diameter, and 275 ns with a 0.5 mm beam diameter.

Figure 6 Variations in modulator transient time response in relation to laser beam diameter for the previous and proposed AOMs at room temperature
Figure 6

Variations in modulator transient time response in relation to laser beam diameter for the previous and proposed AOMs at room temperature

Figure 7 shows the variations in the modulation contrast ratio in relation to the laser beam diameter for the previous and proposed AOMs at room temperature. The modulation contrast ratio for AlInGaAs AOM is 0.3 dB with a 0.1 mm beam diameter, 1.2 dB with a 0.3 mm beam diameter, and 4.8 dB with a 0.5 mm beam diameter. The modulation contrast ratio for SiGeO2 AOM is 0.2 dB with a 0.1 mm beam diameter, 0.8 dB with a 0.3 mm beam diameter, and 3.2 dB with a 0.5 mm beam diameter. The modulation contrast ratio for the previous silicon AOM is 0.1 dB with a 0.1 mm beam diameter, 0.4 dB with a 0.3 mm beam diameter, and 1.6 dB with a 0.5 mm beam diameter.

Figure 7 Variations in modulation contrast ratio in relation to laser beam diameter for the previous and proposed AOMs at room temperature
Figure 7

Variations in modulation contrast ratio in relation to laser beam diameter for the previous and proposed AOMs at room temperature

Figure 8 illustrates the variation in the signal Q Factor in relation to ambient temperature for the previous and proposed AOMs. The Q Factor for AlInGaAs AOM is 15 at room temperature, 8.5 at 375 K, and 3.65 at 450 K. The Q Factor for SiGeO2 AOM is 12 at room temperature, 8 at 375 K, and 3 at 450 K. The Q Factor for the previous silicon AOM is 10 at room temperature, 7 at 375 K, and 2 at 450 K.

Figure 8 Variations in Q Factor in relation to ambient temperature for the previous and proposed AOMs
Figure 8

Variations in Q Factor in relation to ambient temperature for the previous and proposed AOMs

4 Conclusion

We have studied the different AlInGaAs and SiGeO2 acousto optic modulators for upgrading fiber optic communication systems. AlInGaAs AOM presented the highest Q factor, modulation contrast ratio, modulation speed response, and the lowest transient time speed response in comparison to the previous silicon AOM. Modulation frequency, frequency response, and rise time were also evaluated. All of the positive results focused on the proposed AOMs under the same ambient temperature and diameter of laser beam variations. Therefore, AlInGaAs is the best choice for upgrading wideband AO modulators in fiber optic communications.

References

[1] Lee MC, Wu MC. Tunable coupling regimes of silicon microdisk resonators using MEMS actuators. Opt Express. 2006 May;14(11):4703–12.10.1364/OE.14.004703Search in Google Scholar

[2] Shakin OV, Nefedov VG, Churkin PA. Aplication of Acoustooptics in Electronic Devices. Wave Electronics and its Application in Information and Telecommunication Systems. 2018. https://doi.org/10.1109/WECONF.2018.860435110.1109/WECONF.2018.8604351Search in Google Scholar

[3] Chen L, Preston K, Manipatruni S, Lipson M. Integrated GHz silicon photonic interconnect with micrometer-scale modulators and detectors. Opt Express. 2009 Aug;17(17):15248–56.10.1364/OE.17.015248Search in Google Scholar

[4] Ferriai K, Laouari N, Bouaouadia N. Acousto-optic method for liquids refractometry. Opt Appl. 2011;41(1):109–19.Search in Google Scholar

[5] Young Y, Yao E. Design Consideration for Acousto-Optic Devices. Proc IEEE. 2005;69(1):54–11.10.1109/PROC.1982.12248Search in Google Scholar

[6] Johnson RV. Temporal Response of the Acousto Optic Modulator in the High Scattering Eflciency Regime. Applied Optics. 2005; 30 18(3):903-5.10.1364/AO.18.000903Search in Google Scholar PubMed

[7] Limpert J, Deguil-Robin N, Manek-Hnninger I, Salin F, Schreiber T, Liem A, Rser F, Zellmer H, Tünnermann A, Courjaoud A, Hnninger C, and Mottay N. High Power Picosecond Fiber Amplifier Based on Nonlinear Spectral Compression. Opt. Lett. 2005;5 30(3):714-3. https://doi.org/10.1364/OL.30.00071410.1364/OL.30.000714Search in Google Scholar

[8] Datta P, Mukhopadhyay S, Das S, Tartara L, Agnesi A, Degiorgio V. Enhancement of stability and efficiency of a nonlinear mirror mode-locked Nd:YVO(4) oscillator by an active Q-switch. Opt Express. 2004 Aug;12(17):4041–6.10.1364/OPEX.12.004041Search in Google Scholar PubMed

[9] Rashed AN. High Performance Photonic Devices For Multiplexing/Demultiplexing applications in Multi Band Operating Regions. J Comput Theor Nanosci. 2012;9(4):522–9.10.1166/jctn.2012.2055Search in Google Scholar

[10] Zhang X, Song Z, Yu Y, Chen Y, Sun S, Meng Z. Optical Fiber Acoustic Sensor with an All-optical Phase Modulator based on Special Optical Microfiber. International Conference on Optical Mems and Nanophotonics. 2016.Search in Google Scholar

[11] Nikitenko AN, Volkovskiy SA, Mikheev MV, Aleynik AS, Kikilich NE. Influence of Acousto-Optic Resonances in ElectroOptical Modulator on Fiber Optic Gyro Performance and Method for Its Compensation. IEEE Sens J. 2018;18(1):1–7.10.1109/JSEN.2017.2768128Search in Google Scholar

[12] Liu H, Zhang W, Meng L, Yang A, Zeng X. All-fiber Mode Acoustooptic Modulator in Gas Absorption Measurement. 18th International Conference on Optical Communications and Networks. 2018.10.1109/ICOCN.2019.8934883Search in Google Scholar

[13] Qian H, Shao LY, Zhang W, Zhang X, He H, Zou X. Viscosity Measurement Based on Acousto-Optic Effect on Fiber Bragg Grating. Asia Communications and Photonics Conference (ACP). 2017. https://doi.org/10.1364/ACPC.2017.Su2A.8810.1364/ACPC.2017.Su2A.88Search in Google Scholar

[14] Garca G, Flores E, Pntle JA, Italo C, Ernest C. Acoustic Detector all Fiber Optics Using Sagnac Interferometer as modulator of Index Changes of Fiber High Birefringence. Canadian Journal on Electrical and Electronics Engineering. 2011;2(1):8–13.Search in Google Scholar

[15] Rashed AN. Development of Optical Interconnections Modules System Architectures and Its Backplane Technology for Terabit Systems [IJARCSEE]. International Journal of Advanced Research in Computer Science and Electronics Engineering. 2012;1(8):7–17.Search in Google Scholar

[16] Goodman JW. Linear Space Variant Optical Data Processing in Optical Information Processing Fundamentals. Appl Phys (Berl). 2002;48(3):1324–35.Search in Google Scholar

[17] Mayden D. Acousto Optical Pulse Modulators. Journal of Quantum Electronics. 2005;6(1):15–9.10.1109/JQE.1970.1076309Search in Google Scholar

[18] Amiri IS, Rashed AN. Numerical investigation of V shaped three elements resonator for optical closed loop system. Indonesian Journal of Electrical Engineering and Computer Science. 2019;16(3):1392–6.10.11591/ijeecs.v16.i3.pp1392-1397Search in Google Scholar

[19] Alcusa-Sez EP, Dez A, Pérez ER, Margulis W, Norin L, Andrés MV. All-fiber acousto-optic tunable filter in polyimide coated optical fibers. 19th International Conference on Transparent Optical Networks (ICTON). 2017. https://doi.org/10.1109/ICTON.2017.802509310.1109/ICTON.2017.8025093Search in Google Scholar

[20] Alcusa-Sez EP, Dez A, Gonzlez-Herrez M, Andrés MV. Time-resolved acousto-optic interaction in single-mode optical fibers: characterization of axial non uniformities at the nanometer scale. Opt Lett. 2013;39(6):1437–8.10.1364/OL.39.001437Search in Google Scholar PubMed

[21] Alcusa-Sáez EP, Díez A, González-Herráez M, Andrés MV. Improved time-resolved acousto-optic technique for optical fiber analysis of axial non-uniformities by using edge interrogation. Opt Express. 2015 Mar;23(6):7345–50.10.1364/OE.23.007345Search in Google Scholar PubMed

[22] Alcusa-Sáez E, Díez A, Andrés MV. Accurate mode characterization of two-mode optical fibers by in-fiber acousto-optics. Opt Express. 2016 Mar;24(5):4899–905.10.1364/OE.24.004899Search in Google Scholar PubMed

[23] Zhang W, Huang L, Wei K, Li P, Jiang B, Mao D, et al. Cylindrical vector beam generation in fiber with mode selectivity and wave-length tunability over broadband by acoustic flexural wave. Opt Express. 2016 May;24(10):10376–84.10.1364/OE.24.010376Search in Google Scholar PubMed

[24] Carrin-Higueras L, Alcusa-Sez EP, Dez A, Andrés MV. All-fiber laser with intracavity acousto-optic dynamic mode converter. IEEE Photonics J. 2017;9(1):33–6.10.1109/JPHOT.2016.2637566Search in Google Scholar

[25] Andrushchak AS, Mytsyk BG, Demyanyshyn NM, Kaidan MV, Yurkevych OV. Design of optimization technique for electro- and acousto-optical interactions of light in crystalline materials. 9th International Conference on Laser and Fiber-Optical Networks Modeling. 2008. https://doi.org/10.1109/LFNM.2008.467034110.1109/LFNM.2008.4670341Search in Google Scholar

[26] Andrushchak A, Buryy O. The Optimal Geometry of the Acousto Optic Interaction in Selected Crystalline Materials Determined by Extreme Surfaces Method. 8th IEEE International Conference on Advanced Optoelectronics and Lasers (CAOL). 2019. https://doi.org/10.1109/CAOL46282.2019.901951710.1109/CAOL46282.2019.9019517Search in Google Scholar

[27] Mesleh R. AL-Olaimat A. Acousto-Optical Modulators for Free Space Optical Wireless Communication Systems. J. Opt.Commun. 2018;10(5):1–8.10.1364/JOCN.10.000515Search in Google Scholar

[28] Jun Kim H, Song J. Full-Duplex WDM Based ROF System Using All-Optical SSB Frequency Up Conversion and Wavelength Re-Use Techniques. IEEE Trans Microw Theory Tech. 2010;49(2):1354–9.Search in Google Scholar

[29] Chen M, Zhou L, Hara T, Xiao Y, Leung VC. Advances in Multi media Communications. Int J Commun Syst. 2011;24(10):1243–3.10.1002/dac.1349Search in Google Scholar

[30] Genack AZ. Phase Sensitive Detection of Emission and Scattering by Electro Optic Demodulation. J Lumin. 2011;32(2):696–3.10.1016/0022-2313(84)90099-1Search in Google Scholar

[31] Yao X, Maleki L. Optoelectronic oscillators for photonic systems. J. of Quantum Electronics. 1996;32(7):1142–8.10.1109/3.517013Search in Google Scholar

[32] Rashed AN, Tabbour MS. Suitable Optical Fiber Communication Channel for Optical Nonlinearity Signal Processing in High Optical Data Rate Systems. Wireless Personal Communications Journal. 2017;97(1):397–20.10.1007/s11277-017-4511-xSearch in Google Scholar

[33] Rashed AN, Tabour MS, El-Meadawy S. Optimum Flat Gain With Optical Amplification Technique Based on Both Gain Flattening Filters and Fiber Bragg Grating Methods. Journal of Nanoelectronics and Optoelectronics. 2018;13(5):665–13.10.1166/jno.2018.2168Search in Google Scholar

[34] Rashed AN, Tabbour MS. The Trade Off Between Different Modulation Schemes for Maximum Long Reach High Data Transmission Capacity Optical Orthogonal Frequency Division Multiplexing (OOFDM). Wireless Personal Communications Journal. 2018;101(1):325–13.10.1007/s11277-018-5690-9Search in Google Scholar

[35] Rashed AN, Mohammed A, Zaky WF, Amiri IS, Yupapin P. The switching of optoelectronics to full optical computing operations based on nonlinear metamaterials. Results Phys. 2019;13:102152.10.1016/j.rinp.2019.02.088Search in Google Scholar

[36] Amiri IS, Houssien FM, Rashed AN, Mohammed AA. Temperature effects on characteristics and performance of near-infrared wide bandwidth for different avalanche photodiodes structures. Results Phys. 2019;14:102399.10.1016/j.rinp.2019.102399Search in Google Scholar

[37] Amiri IS, Rashed ANZ, Yupapin P. Mathematical Model Analysis of Dispersion and Loss in Photonic Crystal Fibers. Journal of Optical Communications. Published online: April 2019. https://doi.org/10.1515/joc-2019-005210.1515/joc-2019-0052Search in Google Scholar

[38] Amiri IS, Rashed ANZ, Yupapin P. Basic Functions of Fiber Bragg Grating Effects on the Optical Fiber Systems Performance Efficiency. Journal of Optical Communications. Published Online: 5 April 2019. https://doi.org/10.1515/joc-2019-004210.1515/joc-2019-0042Search in Google Scholar

[39] Amiri IS, Rashed ANZ, Mohammed AA, Aboelazm MB, Yupapin P. Nonlinear Effects with Semiconductor Optical Amplifiers. Journal of Optical Communications. Published Online: 12 April 2019. https://doi.org/10.1515/joc-2019-005310.1515/joc-2019-0053Search in Google Scholar

[40] Amiri IS, Rashed ANZ, Yupapin P. High-Speed Light Sources in High-Speed Optical Passive Local Area Communication Networks. Journal of Optical Communications. Published Online: 20 April 2019. https://doi.org/10.1515/joc-2019-007010.1515/joc-2019-0070Search in Google Scholar

[41] Amiri IS, Rashed ANZ, Mohammed AA, El-Din ES, Yupapin P. Spatial Continuous Wave Laser and Spatiotemporal VCSEL for High Speed Long Haul Optical Wireless Communication Channels. Journal of Optical Communications. Published Online: 24 April 2019. https://doi.org/10.1515/joc-2019-006110.1515/joc-2019-0061Search in Google Scholar

[42] Amiri IS, Rashed ANZ, Yupapin P. Average Power Model of Optical Raman Amplifiers Based on Frequency Spacing and Amplifier Section Stage Optimization. Journal of Optical Communications. Published Online: 4 May 2019. https://doi.org/10.1515/joc-2019-008110.1515/joc-2019-0081Search in Google Scholar

[43] Amiri IS, Rashed ANZ. Power Enhancement of the U-shape Cavity Microring Resonator Through Gap and Material Characterizations. Journal of Optical Communications. Published Online: 19 Oct. 2019. https://doi.org/https://doi.org/10.1515/joc-2019-010810.1515/joc-2019-0108Search in Google Scholar

Received: 2020-04-04
Accepted: 2020-05-11
Published Online: 2020-06-10

© 2020 H. M. El-Hageen et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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