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Intelligent Modeling of the Ionosphere and Troposphere for Radio Application...
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Intelligent Modeling of the Ionosphere and Troposphere for Radio Application (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 839

Special Issue Editors

Dr. Jian Wang

E-Mail Website
Guest Editor
School of Microelectronics, Tianjin University, Tianjin 300072, China
Interests: space weather; intelligent modeling; radio propagation; wireless communication
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yu Zheng

E-Mail Website
Guest Editor
College Electronic Information, Qingdao University, Qingdao 266071, China
Interests: ionospheric monitoring; space environment; radio propagation; inverse problem
Special Issues, Collections and Topics in MDPI journals
Dr. Jieqing Fan

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Interests: intelligent modeling; radio propagation; THz communication
Special Issues, Collections and Topics in MDPI journals
Dr. Na Li

E-Mail Website
Guest Editor
School of Electronic Science and Technology, Hainan University, Haikou 570228, China
Interests: space weather; space physics; space detection; radio propagation
Dr. Cheng Yang

E-Mail Website
Guest Editor
School of Microelectronics, Tianjin University, Tianjin 300072, China
Interests: radio propagation; maritime communications; modeling in the troposphere

Special Issue Information

Dear Colleagues,

This Special Issue is the second edition in a series of publications dedicated to “Intelligent Modeling of the Ionosphere and Troposphere for Radio Application”.

Since the latter half of the 20th century, the rapid advancement of wireless communication technology has profoundly influenced every facet of daily life, creating an imperative and practical demand for comprehending the space weather in the cognitive realm and acquiring expertise in the principles of radio wave propagation. In recent decades, substantial achievements have been accomplished in space weather science and radio wave propagation research. However, complex challenges persist due to this field's interdisciplinary nature and extensive investigation scope, awaiting resolution. Moreover, introducing artificial intelligence technology has further invigorated space weather science and radio wave propagation, positioning them as vibrant and burgeoning disciplines.

This Special Issue aims to improve our understanding of the characteristics of the electromagnetic environment and electromagnetic wave propagation in the ionosphere and troposphere for radio applications using intelligent modeling techniques. To develop a deeper insight into coupling processes between electromagnetic environment and electromagnetic wave propagation, this Special Issue will focus on observations, models, simulations, innovative algorithms, and intelligent modeling techniques applied in the solar activity, ionosphere, troposphere, and its multiphysics coupling.

This Special Issue welcomes papers that discuss innovative multidisciplinary and multiparameter methods and applications for modeling phenomena in solar activity, the ionosphere, and the troposphere, as well as their possible interactions and signatures of electromagnetic effect.

Dr. Jian Wang
Prof. Dr. Yu Zheng
Dr. Jieqing Fan
Dr. Na Li
Dr. Cheng Yang
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. Atmosphere is an international peer-reviewed open access monthly 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 2400 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.

Keywords

  • ionosphere
  • troposphere
  • solar activity
  • space weather
  • radio propagation
  • ground-based and satellite observations
  • intelligent modeling
  • multiphysics coupling
  • natural geo-hazard

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Published Papers (1 paper)

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Research

19 pages, 4555 KiB  
Article
An Intelligent Decision-Making for Electromagnetic Spectrum Allocation Method Based on the Monte Carlo Counterfactual Regret Minimization Algorithm in Complex Environments
by Guoqin Kang, Ming Tan, Xiaojun Zou, Xuguang Xu, Lixun Han and Hainan Du
Atmosphere 2025, 16(3), 345; https://doi.org/10.3390/atmos16030345 - 20 Mar 2025
Viewed by 376
Abstract
In modern communication, the electromagnetic spectrum serves as the carrier for information transmission, and the only medium enabling information exchange anywhere, anytime. To adapt to the changing dynamics of a complex electromagnetic environment, electromagnetic spectrum allocation algorithms must not only meet the demands [...] Read more.
In modern communication, the electromagnetic spectrum serves as the carrier for information transmission, and the only medium enabling information exchange anywhere, anytime. To adapt to the changing dynamics of a complex electromagnetic environment, electromagnetic spectrum allocation algorithms must not only meet the demands for efficiency and intelligence but also possess anti-jamming capabilities to achieve the best communication effect. Focusing on intelligent wireless communication, this paper proposes a multi-agent hybrid game spectrum allocation method under incomplete information and based on the Monte Carlo counter-factual regret minimization algorithm. Specifically, the method first utilizes frequency usage and interference information from both sides to train agents through extensive simulations using the Monte Carlo Method, allowing the trial values to approach the expected values. Based on the results of each trial, the counterfactual regret minimization algorithm is employed to update the frequency selection strategies for both the user and the interferer. Subsequently, the trained agents from both sides engage in countermeasure communication. Finally, the probabilities of successful communication and successful interference for both sides are statistically analyzed. The results show that under the multi-agent hybrid game spectrum allocation method based on the Monte Carlo counter-factual regret minimization algorithm, the probability of successful interference against the user is 32.5%, while the probability of successful interference by the jammer is 37.3%. The average simulation time per round is 3.06 s. This simulation validates the feasibility and effectiveness of the multi-agent hybrid game spectrum allocation module based on the Monte Carlo counter-factual regret minimization algorithm. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application (2nd Edition))
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