Hybrid Optical Sensing and
Communication Over a Multicore Fiber
Item Type Conference Paper
Authors Guo, Yujian;Ashry, Islam;Trichili, Abderrahmen;Mao, Yuan;Mosquera, Juan Marin;Ng, Tien Khee;Ooi, Boon S.
Citation Guo, Y., Ashry, I., Trichili, A., Mao, Y., Mosquera, J. M., Ng, T. K., &
Ooi, B. S. (2022). Hybrid Optical Sensing and Communication Over a Multicore Fiber. 27th International Conference on Optical Fiber Sensors. https://doi.org/10.1364/ofs.2022.th4.30
Eprint version Post-print
DOI 10.1364/OFS.2022.Th4.30
Publisher Optica Publishing Group
Rights This is an accepted manuscript version of a paper before final publisher editing and formatting. Archived with thanks to Optica Publishing Group.
Download date 2023-12-23 20:15:17
Link to Item http://hdl.handle.net/10754/689480
Hybrid Optical Sensing and Communication Over a Multicore Fiber
Yujian Guo1, Islam Ashry1, Abderrahmen Trichili1, Yuan Mao1,2, Juan Marin Mosquera1, Tien Khee Ng1, and Boon S. Ooi1,*
1Computer, Electrical and Mathematical Sciences Division at King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah Province, Kingdom of Saudi Arabia
2Zhongshan Institute of Changchun University of Science and Technology, Guangdong, 528400, China
Abstract: We demonstrate a full–duplex data transmission simultaneously with a dis- tributed acoustic sensing and a fiber Bragg grating–based temperature sensing over a mul- ticore fiber. The communication and sensing systems operate efficiently with negligible crosstalks. © 2022 The Author(s)
1. Introduction
Optical fiber networks form the communication infrastructure backbone of our modern society, allowing the trans- fer of a tremendous amount of data at nearly the speed of light. Increasing the transmission capacity of optical fibers to keep up with the steady increase of bandwidth demand can be done through spatial division multiplex- ing over multicore fibers (MCFs) [1]. As optical fiber distributed acoustic sensor (DAS) and fiber Bragg grating (FBG)–based single–point temperature sensor have been deployed in various applications [2,3], designing a hy- brid communication and sensing system using optical fiber telecommunication networks is very beneficial. Adding the sensing functionalities can turn optical fibers used for communication, including those underwater, into large sensors. The network of millions of submerged kilometers of fibers crisscrossing the oceans can become an invalu- able tool for measuring earthquakes and monitoring climate change parameters. Researchers have already started studying incorporating sensing techniques with communication over the same optical fibers [4,5]. With all that said, using next–generation MCFs for simultaneous high–speed communication and sensing can open a plethora of opportunities without incurring additional costs.
In this work, we report on a hybrid full–duplex (FD) fiber communication, fiber–optic DAS, and FBG–based temperature sensor over the same∼1.2–km–long seven–core MCF. Two cores of the MCF are used to establish the FD communication, another core for DAS, and two other cores for FBG–based temperature sensing. A data rate of 3.2 Gbit/s fiber communication with bit error ratio (BER) of 1.8×10−4and 2.8×10−4of two channels are achieved using an on–off keying (OOK) modulation scheme. Meanwhile, the fiber–optic DAS system identifies the location and frequency of a vibration event produced by a piezoelectric transducer (PZT) attached to the fiber. Along with the communication and DAS system, the FBG–based sensor measures the temperature at a user–end. The communication links were robust to the noise and interference from the DAS and FBG channels with BERs below the forward error correction (FEC) limit. These results represent a firm step forward in using telecommunication fibers for simultaneous communication and distributed sensing.
2. Hybrid Fiber–Optic Communication and Sensing System
The setup for the hybrid fiber communication and sensing system is shown in Fig.1. Five out of seven cores of an MCF (from YOFC) are used. Two cores are used to establish the FD communication, one core for DAS, and two cores for FBG–based temperature sensing. As shown in Fig. 1, the communication configuration per link comprises a high–performance serial bit error rate tester (J–BERT N4903B, Agilent) for the generation of OOK–
modulated signals. The modulated signals are then carried by an optical beam emitted from a 1550–nm pigtailed–
fiber laser (LP1550–SAD2, Thorlabs), which is biased by a laser driver (ITC4005, Thorlabs) and coupled to the MCF throughout a fan–in/out. The optical signals are received by a balanced photodetector (PD) (PDB480C–AC, Thorlabs) at the other end of MCF. A digital communication analyzer (DCA–J 86100C, Agilent) connected to the PD is used to analyze the received signals and evaluate communication performance per link.
Fig.1 also shows the FBG–based temperature sensing configuration, where a broadband laser source is con- nected to a core of the MCF. At the opposite end of the MCF, a U-turn-shaped FBG is connected to the same core and another unused core. The temperature at the FBG location can be extracted by monitoring the spectral transmissivity of the FBG, after its initial calibration [6,7]. The optical power spectrum of the transmitted light through the FBG is analyzed by an optical spectrum analyzer (OSA) (AQ6370B, Yokogawa)
In the DAS unit, shown in Fig.1, a 1550-nm narrow linewidth laser generates a continuous–wave (CW) light, which is modulated into optical pulses using an acousto–optic modulator (AOM). The pulses are then amplified by an erbium–doped fiber amplifier (EDFA) and then injected into a core of the MCF through a circulator and the fan–in/out, respectively. A∼5–m MCF section is wound around a PZT cylinder, driven by an arbitrary waveform generator (81150A, Agilent) to generate predetermined vibrations at a position along the MCF. The backscattered Rayleigh signal from the MCF is circulated to another EDFA (EDFA2), which amplified spontaneous emission (ASE) is discarded using a FBG. The filtered Rayleigh signals are then detected by a PD and sampled using a data acquisition device (DAQ).
Fig. 1. Experimental system configuration of the hybrid sensing and communication system over the MCF. BERT: bit error rate tester, Clk: clock, DCA: digital communication analyzer, PD: photode- tector, OSA: optical spectrum analyzer, EDFA: Erbium doped fiber amplifier, AOM: acousto–optic modulator, CW: continuous wave, Circ: circulator, FBG: fiber Bragg grating, DAQ: data acquisition, SMF: single–mode fiber.
3. Results
The measured eye–diagrams of the two communication channels at a data rate of 3.2 Gbit/s OOK (per link) and with BER values of 1.8−4and 2.8×10−4, while running the DAS and FBG–based temperature sensing system, are shown in Figs.2(a) and (b), respectively. Running the DAS and FBG–based temperature sensing system in adjacent cores introduces noise to the communication channels. However, the obtained BERs are below the FEC limit, and the open eye patterns indicate minimal signal distortion from channel noise and interference from the DAS and FBG cores. These results prove the robustness of the communication system over the MCF.
In Figs.2(c) and (d), detecting the location and frequency of the PZT vibration event are shown. Using the normalized differential method [8] to process the backscattered Rayleigh traces from the MCF, the vibration position can be accurately identified (Figs. 2(c)). Applying the fast Fourier transform (FFT) on the temporal vibration data, we accurately calculate the vibration frequency (500 Hz in Figs.2(d)), which matches that of the PZT.
Fig.2(e) depicts the spectral shift of the FBG transmissivity with the temperature changes. Obviously, the FBG can be used to measure the temperature at the end–user. The FBG could also be installed at any position along the MCF, using a fan–in/out. The overall results confirm the ability of the designed system to provide simultaneous communication, distributed vibration sensing, and point temperature sensing using the MCF.
4. Conclusion
We present a new design for a hybrid communication, DAS, and FBG–based temperature sensing system over an MCF. As a proof of concept demonstration, we report a successful FD communication at 3.2 Gbit/s with a
Fig. 2. (a) and (b) Eye diagrams of the OOK transmission at a data rate of 3.2 Gbit/s through the two channels; (c) PZT vibration location and power spectrum; (d) Measured DAS frequency; (e) FBG wavelength shift due to temperature variance.
BER per link, which is below the FEC limit, while monitoring vibrations of 500 Hz frequency using the DAS and 4◦C, 18◦C, and 65◦C temperatures with the FBG. We believe that the reported design will pave the way toward convergence of communication and sensing over the same fiber network.
References
1. D. J. Richardson, J. M. Fini, and L. E. Nelson, “Space–division multiplexing in optical fibres,” Nat. Photon.7, 354—362 (2013).
2. H. Gabai and A. Eyal,“On the sensitivity of distributed acoustic sensing,” Opt. Lett.41, 5648–5651 (2016).
3. G. Li, L. Ji, G. Li, J. Su, and C. Wu, “High-resolution and large–dynamic–range temperature sensor using fiber Bragg grating Fabry-P´erot cavity,” Opt. Express29, 18523–18529 (2021).
4. Y. Yan, H. Zheng, Z. Zhao, C.Guo, X. Wu, J. Hu, A.P.T. Lau, and C Lu, “Distributed optical fiber sensing assisted by optical communication techniques,” J. Light. Technol.39, 3654-3670 (2021).
5. C. Dorize, S. Guerrier, E. Awwad, P. A. Nwakamma, H. Mardoyan, and J. Renaudier, “An OFDM–MIMO distrib- uted acoustic sensing over deployed telecom fibers,” in Optical Fiber Communication Conference (OFC) 2021, paper W7C.2.
6. J. Wen, J. Wang, L. Yang, Y. Hou, D. Huo, E. Cai, Y. Xiao, S. Wang, “Response time of microfiber temperature sensor in liquid environment,” IEEE Sensors J.20, 6400—6407 (2020).
7. Q. Chen, D. N. Wang, and F. Gao, “Simultaneous refractive index and temperature sensing based on a fiber surface waveguide and fiber Bragg gratings,” Opt. Lett.46, 1209–1212 (2021).
8. I. Ashry, Y. Mao, M. S. Alias, T. K. Ng, F. Hveding, M. Arsalan, and B. S. Ooi, “Normalized differential method for improving the signal–to–noise ratio of a distributed acoustic sensor,” Appl. Opt.58, 4933–4938 (2019).