IOT-Based Injection-Locked Microwave Photonic Frequency Division Signal Processing
When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division s...
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Published in | Mobile information systems Vol. 2022; pp. 1 - 10 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Hindawi
27.09.2022
John Wiley & Sons, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1574-017X 1875-905X |
DOI | 10.1155/2022/1351399 |
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Abstract | When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division signal processing effect needs more research and exploration. Taking the traditional mode architecture as a reference, this paper constructs an injection-locked microwave photonic frequency division signal processing model based on the Internet of Things. In this paper, the popular deep analysis method is used to optimize the model, and the photonic technology is matched with the microwave analysis. The purpose of this construction is to weaken the microwave integration error and improve the calculation accuracy to a higher level. In addition, aiming at the difficult problem of microwave signal generation, this paper uses the optical injection method to lock the microwave photons and generate waveform signals, which makes the model data more representative, so as to solve the problems of unstable microwave signals and high transmission costs. This paper also discusses the possibility of microwave photon filtering and frequency division signal processing of microwaves. The optimal solution is determined by analyzing the experimental results of various technical means, thus proving that the injection-locked microwave photonic frequency division signal processing means has better stability and a higher fitting degree. |
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AbstractList | When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division signal processing effect needs more research and exploration. Taking the traditional mode architecture as a reference, this paper constructs an injection-locked microwave photonic frequency division signal processing model based on the Internet of Things. In this paper, the popular deep analysis method is used to optimize the model, and the photonic technology is matched with the microwave analysis. The purpose of this construction is to weaken the microwave integration error and improve the calculation accuracy to a higher level. In addition, aiming at the difficult problem of microwave signal generation, this paper uses the optical injection method to lock the microwave photons and generate waveform signals, which makes the model data more representative, so as to solve the problems of unstable microwave signals and high transmission costs. This paper also discusses the possibility of microwave photon filtering and frequency division signal processing of microwaves. The optimal solution is determined by analyzing the experimental results of various technical means, thus proving that the injection-locked microwave photonic frequency division signal processing means has better stability and a higher fitting degree. |
Author | Wang, Guangying Chen, Jingxu Wang, Lin |
Author_xml | – sequence: 1 givenname: Lin orcidid: 0000-0002-2508-5405 surname: Wang fullname: Wang, Lin organization: School of Electronic and Electrical EngineeringZhaoqing UniversityZhaoqing 526061Chinazqu.edu.cn – sequence: 2 givenname: Guangying orcidid: 0000-0002-1654-7460 surname: Wang fullname: Wang, Guangying organization: Institute of Photonics TechnologyJinan UniversityGuangzhou 510632Chinajnu.edu.cn – sequence: 3 givenname: Jingxu orcidid: 0000-0002-0085-9742 surname: Chen fullname: Chen, Jingxu organization: Institute of Photonics TechnologyJinan UniversityGuangzhou 510632Chinajnu.edu.cn |
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CitedBy_id | crossref_primary_10_1109_JSEN_2024_3367963 |
Cites_doi | 10.1063/1.1148382 10.1109/TNSE.2019.2917071 10.1109/tmtt.2010.2076932 10.1016/j.jfoodeng.2012.03.013 10.1117/1.oe.59.8.087104 10.1109/22.989980 10.1016/j.suscom.2022.100773 10.1109/tps.2002.801653 10.1063/1.3231874 10.1109/tim.2010.2045552 10.1109/jssc.2006.880592 10.1109/wamicon.2015.7120431 10.1016/j.comcom.2019.10.035 10.1002/mop.20537 10.1109/JIOT.2020.3026730 10.1007/978-4-431-55148-5_5 10.1038/nphoton.2007.89 10.1002/lpor.201200032 10.1038/s41566-018-0310-5 10.1177/1468087418810587 |
ContentType | Journal Article |
Copyright | Copyright © 2022 Lin Wang et al. Copyright © 2022 Lin Wang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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SubjectTerms | Diodes Energy Frequency locking Interdisciplinary subjects Internet of Things Lasers Microwave communications Microwave photonics Network switching Optics Optimization Photonics Photons Sensors Signal generation Signal processing Waveforms Wireless communications |
Title | IOT-Based Injection-Locked Microwave Photonic Frequency Division Signal Processing |
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