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Advanced Infocomm Technology including Selected Papers from 14th ICAIT 2022

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 8371

Special Issue Editors


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Guest Editor
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: photonics; optical fiber sensors; fiber acoustic detection; gas detection
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: photonics; optical fiber sensors; fiber acoustic detection; gas detection

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Guest Editor
Institute of Laser Spectroscopy, Shanxi University, Taiyuan 030006, China
Interests: photoacoustic spectrometry; photothermal spectroscopy; laser applications in environmental monitoring; industrial process control and medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We cordially invite you to contribute to this Special Issue of the journal Sensors devoted to the latest findings in optical communication, optical sensing and imaging, and relevant technologies. In addition, a few highly qualified papers selected and extended in the framework of the 2022 IEEE 14th International Conference on Advanced Infocomm Technology (ICAIT) will be included in this Special Issue. ICAIT 2022 will be held online on 8–11 July 2022 in Chongqing, China, (http://www.icait.org/index.html).

The topics of this Special Issue include, but are not limited to wireless communication and networks, optical fiber communication and networks, space communications, navigation and tracking, fiber and sensor technologies, microwave photonics, micro- and nano-optical devices and sensing, fiber laser technologies and applications, optical imaging technologies and applications, signal, information and data processing for communications, semiconductor optoelectronic devices, and photoacoustic detection technologies and applications.

Prof. Dr. Ping Lu
Dr. Chaotan Sima
Prof. Dr. Hongpeng Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

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13 pages, 3864 KiB  
Communication
A Computational Model of Cn2 Profile Inversion for Atmospheric Laser Communication in the Vertical Path
by Haifeng Yao, Yuxi Cao, Weihao Wang, Qingfang Jiang, Jie Cao, Qun Hao, Zhi Liu, Peng Zhang, Yidi Chang, Guiyun Zhang and Tongtong Geng
Sensors 2023, 23(13), 5874; https://doi.org/10.3390/s23135874 - 25 Jun 2023
Viewed by 1119
Abstract
In this paper, an atmospheric structure constant Cn2 model is proposed for evaluating the channel turbulence degree of atmospheric laser communication. First, we derive a mathematical model for the correlation between the atmospheric coherence length r0, the isoplanatic angle [...] Read more.
In this paper, an atmospheric structure constant Cn2 model is proposed for evaluating the channel turbulence degree of atmospheric laser communication. First, we derive a mathematical model for the correlation between the atmospheric coherence length r0, the isoplanatic angle θ0 and Cn2 using the Hufnagel–Valley (HV) turbulence model. Then, we calculate the seven parameters of the HV model with the actual measured r0 and θ0 data as input quantities, so as to draw the Cn2 profile and the θ0 profile. The experimental results show that the fitted average Cn2 contours and single-day Cn2 contours have superior fitting performance compared with our historical data, and the daily correlation coefficient between the single-day computed θ0 contours and the measured θ0 contours is up to 87%. This result verifies the feasibility of the proposed method. The results validate the feasibility of the proposed method and provide a new technical tool for the inversion of turbulence Cn2 profiles. Full article
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13 pages, 2980 KiB  
Communication
LSTM Attention Neural-Network-Based Signal Detection for Hybrid Modulated Faster-Than-Nyquist Optical Wireless Communications
by Minghua Cao, Ruifang Yao, Jieping Xia, Kejun Jia and Huiqin Wang
Sensors 2022, 22(22), 8992; https://doi.org/10.3390/s22228992 - 20 Nov 2022
Cited by 4 | Viewed by 1758
Abstract
In order to improve the accuracy of signal recovery after transmitting over atmospheric turbulence channel, a deep-learning-based signal detection method is proposed for a faster-than-Nyquist (FTN) hybrid modulated optical wireless communication (OWC) system. It takes advantage of the long short-term memory (LSTM) network [...] Read more.
In order to improve the accuracy of signal recovery after transmitting over atmospheric turbulence channel, a deep-learning-based signal detection method is proposed for a faster-than-Nyquist (FTN) hybrid modulated optical wireless communication (OWC) system. It takes advantage of the long short-term memory (LSTM) network in the recurrent neural network (RNN) to alleviate the interdependence problem of adjacent symbols. Moreover, an LSTM attention decoder is constructed by employing the attention mechanism, which can alleviate the shortcomings in conventional LSTM. The simulation results show that the bit error rate (BER) performance of the proposed LSTM attention neural network is 1 dB better than that of the back propagation (BP) neural network and outperforms by 2.5 dB when compared with the maximum likelihood sequence estimation (MLSE) detection method. Full article
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10 pages, 6169 KiB  
Article
Optical Fiber Sensor for Curvature and Temperature Measurement Based on Anti-Resonant Effect Cascaded with Multimode Interference
by Yinqiu Gui, Qian Shu, Ping Lu, Jiajun Peng, Jiangshan Zhang and Deming Liu
Sensors 2022, 22(21), 8457; https://doi.org/10.3390/s22218457 - 3 Nov 2022
Cited by 5 | Viewed by 1437
Abstract
In this paper, a novel inline optical fiber sensor for curvature and temperature measurement simultaneously has been proposed and demonstrated, which can measure two parameters with very little crosstalk. Two combinational mechanisms of anti-resonant reflecting optical waveguide and inline Mach–Zehnder interference structure are [...] Read more.
In this paper, a novel inline optical fiber sensor for curvature and temperature measurement simultaneously has been proposed and demonstrated, which can measure two parameters with very little crosstalk. Two combinational mechanisms of anti-resonant reflecting optical waveguide and inline Mach–Zehnder interference structure are integrated into a 3 mm-long single hole twin suspended core fiber (SHTSCF). The 85 μm hole core gives periodic several dominant resonant wavelengths in the optical transmission spectrum, acting as the anti-resonant reflecting optical waveguide (ARROW). The modes in two suspended cores and the cladding form the comb pattern. Reliable sensor sensitivity can be obtained by effective experiments and demodulation. Through intensity demodulation of the selected dip of Gaussian fitting, the curvature sensitivity can be up to −7.23 dB/m−1. Through tracking the MZI dip for wavelength demodulation, the temperature sensitivity can be up to 28.8 pm/°C. The sensor is simple in structure, compact, and has good response, which can have a bright application in a complex environment. Full article
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9 pages, 3700 KiB  
Communication
Optical Gas-Cell Dynamic Adsorption in a Photoacoustic Spectroscopy-Based SOF2 and SO2F2 Gas Sensor
by Ying Zhang, Mingwei Wang, Pengcheng Yu and Zhe Liu
Sensors 2022, 22(20), 7949; https://doi.org/10.3390/s22207949 - 18 Oct 2022
Cited by 4 | Viewed by 1330
Abstract
SO2F2 and SOF2 are the main components from the decomposition of insulation gas SF6. Photoacoustic spectroscopy (PAS) has been acknowledged as an accurate sensing technique. Polar material adsorption for SO2F2 and SOF2 in [...] Read more.
SO2F2 and SOF2 are the main components from the decomposition of insulation gas SF6. Photoacoustic spectroscopy (PAS) has been acknowledged as an accurate sensing technique. Polar material adsorption for SO2F2 and SOF2 in the photoacoustic gas cell of PAS may affect detection efficiency. In this paper, the optical gas-cell dynamic adsorptions of four different materials and the detection effects on SO2F2 and SOF2 are theoretically analyzed and experimentally demonstrated. The materials, including grade 304 stainless steel (SUS304), grade 6061 aluminum alloy (Al6061), polyvinylidene difluoride (PVDC), and polytetrafluoroethylene (PTFE), were applied inside the optical gas cell. The results show that, compared with metallic SUS304 and Al6061, plastic PVDC and PTFE would reduce the gas adsorption of SO2F2 and SOF2 by 10 to 20% and shorten the response time during gas exchange. The complete gas defusing period in the experiment was about 30 s. The maximum variations of the 90% rising time between the different adsorption materials were approximately 3 s for SO2F2 and 6 s for SOF2, while the generated photoacoustic magnitudes were identical. This paper explored the material selection for PAS-based gas sensing in practical applications. Full article
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Review

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16 pages, 3439 KiB  
Review
Ultrasensitive Optical Fiber Sensors Working at Dispersion Turning Point: Review
by Shengyao Xu, Peng Kang, Zhijie Hu, Weijie Chang and Feng Huang
Sensors 2023, 23(3), 1725; https://doi.org/10.3390/s23031725 - 3 Feb 2023
Cited by 3 | Viewed by 2123
Abstract
Optical fiber sensors working at the dispersion turning point (DTP) have served as promising candidates for various sensing applications due to their ultrahigh sensitivity. In this review, recently developed ultrasensitive fiber sensors at the DTP, including fiber couplers, fiber gratings, and interferometers, are [...] Read more.
Optical fiber sensors working at the dispersion turning point (DTP) have served as promising candidates for various sensing applications due to their ultrahigh sensitivity. In this review, recently developed ultrasensitive fiber sensors at the DTP, including fiber couplers, fiber gratings, and interferometers, are comprehensively analyzed. These three schemes are outlined in terms of operation principles, device structures, and sensing applications. We focus on sensitivity enhancement and optical transducers, we evaluate each sensing scheme based on the DTP principle, and we discuss relevant challenges, aiming to provide some clues for future research. Full article
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