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Recent Advances in Artificial Intelligence Applications in Radio Propagation for Communications

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

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 6372

Special Issue Editors

Dr. Mohammad Alibakhshikenari

E-Mail Website
Guest Editor
Electronics Engineering Department, University of Rome “Tor Vergata”, 00133 Rome, Italy
Interests: antennas and wave-propagations; array antennas; metamaterials and metasurfaces; synthetic aperture radars (SAR); multiple-input multiple-output (MIMO) systems; waveguide slotted antenna arrays; substrate integrated waveguides (SIWs); antenna impedance matching networks; filters; on-chip antennas; microwave; millimeter-waves and terahertz applications; terahertz integrated circuits; and electromagnetic compatibilities
Special Issues, Collections and Topics in MDPI journals
Dr. Giovanni Pau

E-Mail Website
Guest Editor
Faculty of Engineering and Architecture, Kore University of Enna, 94100 Enna, Italy
Interests: wireless sensor networks; intelligent transportation systems; Internet of Things; green communications; fuzzy logic
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Expanding wireless data capacity is pushing past the performance limit of wireless communication systems. This increasing amount of data presents looming challenges. Consequently, future wireless communications will demand robust and thoughtful solutions to attain additional usefulness in various scenarios. In this time of big data, where data mining and data investigation methods are applicable procedures for system development and testing, Artificial Intelligence (AI) applications in wireless communications are receiving considerable attention. AI delivers unique resolutions for the complicated issue of arranging communication systems. Moreover, it represents a powerful tool and a widespread examination subject, with multiple conceivable applications to improve wireless communications. Radio propagation is essential for the arrangement and performance investigation of any wireless communication system. Several solutions related to AI can be applied in this research field. For instance, clustering algorithms are widely employed for propagation channel feature extraction. Likewise, innovative learning-based radio channel prediction techniques are obtaining significant importance in communication system development and evaluation.

This Special Issue invites the submission of high-quality articles describing AI applications in radio propagation for communications. These papers should focus on resolving problems and challenges typical of AI applications in radio propagation for communications, introducing and combining innovative methods efficiently, and presenting the performance evaluation with existing approaches. Both theoretical and experimental studies are welcome, along with high-quality review papers.

Topics of interest for articles include, but are not limited to:

  • Innovative AI-based solutions for radio propagation description and examination.
  • Clustering investigation for radio channel description and modeling.
  • AI technique development and testing in radio propagation for applications in wireless communications.
  • AI applications for channel modeling and communication system simulation.
  • Data investigation and parameter extractions of wireless channels assisted by AI-based methods.
  • Smart antenna systems with beamforming capabilities.

Dr. Mohammad Alibakhshikenari
Dr. Giovanni Pau
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.

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Published Papers (2 papers)

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Research

15 pages, 5858 KiB  
Article
Design of a Planar Sensor Based on Split-Ring Resonators for Non-Invasive Permittivity Measurement
by Mohammad Alibakhshikenari, Bal S. Virdee, Taha A. Elwi, Innocent D. Lubangakene, Renu K. R. Jayanthi, Amer Abbood Al-Behadili, Zaid A. Abdul Hassain, Syed Mansoor Ali, Giovanni Pau, Patrizia Livreri and Sonia Aïssa
Sensors 2023, 23(11), 5306; https://doi.org/10.3390/s23115306 - 2 Jun 2023
Cited by 13 | Viewed by 3149
Abstract
The permittivity of a material is an important parameter to characterize the degree of polarization of a material and identify components and impurities. This paper presents a non-invasive measurement technique to characterize materials in terms of their permittivity based on a modified metamaterial [...] Read more.
The permittivity of a material is an important parameter to characterize the degree of polarization of a material and identify components and impurities. This paper presents a non-invasive measurement technique to characterize materials in terms of their permittivity based on a modified metamaterial unit-cell sensor. The sensor consists of a complementary split-ring resonator (C-SRR), but its fringe electric field is contained with a conductive shield to intensify the normal component of the electric field. It is shown that by tightly electromagnetically coupling opposite sides of the unit-cell sensor to the input/output microstrip feedlines, two distinct resonant modes are excited. Perturbation of the fundamental mode is exploited here for determining the permittivity of materials. The sensitivity of the modified metamaterial unit-cell sensor is enhanced four-fold by using it to construct a tri-composite split-ring resonator (TC-SRR). The measured results confirm that the proposed technique provides an accurate and inexpensive solution to determine the permittivity of materials. Full article
(This article belongs to the Special Issue Recent Advances in Artificial Intelligence Applications in Radio Propagation for Communications)
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20 pages, 7163 KiB  
Article
Acoustic Wave Reflection in Water Affects Underwater Wireless Sensor Networks
by Kaveripakam Sathish, Monia Hamdi, Ravikumar Chinthaginjala Venkata, Mohammad Alibakhshikenari, Manel Ayadi, Giovanni Pau, Mohamed Abbas and Neeraj Kumar Shukla
Sensors 2023, 23(11), 5108; https://doi.org/10.3390/s23115108 - 26 May 2023
Cited by 14 | Viewed by 2194
Abstract
The phenomenon of acoustic wave reflection off fluid–solid surfaces is the focus of this research. This research aims to measure the effect of material physical qualities on oblique incidence acoustic attenuation across a large frequency range. To construct the extensive comparison shown in [...] Read more.
The phenomenon of acoustic wave reflection off fluid–solid surfaces is the focus of this research. This research aims to measure the effect of material physical qualities on oblique incidence acoustic attenuation across a large frequency range. To construct the extensive comparison shown in the supporting documentation, reflection coefficient curves were generated by carefully adjusting the porousness and permeability of the poroelastic solid. The next stage in determining its acoustic response is to determine the pseudo-Brewster angle shift and the reflection coefficient minimum dip for the previously indicated attenuation permutations. This circumstance is made possible by modeling and studying the reflection and absorption of acoustic plane waves encountering half-space and two-layer surfaces. For this purpose, both viscous and thermal losses are taken into account. According to the research findings, the propagation medium has a significant impact on the form of the curve that represents the reflection coefficient, whereas the effects of permeability, porosity, and driving frequency are relatively less significant to the pseudo-Brewster angle and curve minima, respectively. This research additionally found that as permeability and porosity increase, the pseudo-Brewster angle shifts to the left (proportionally to porosity increase) until it reaches a limiting value of 73.4 degrees, and that the reflection coefficient curves for each level of porosity exhibit a greater angular dependence, with an overall decrease in magnitude at all incident angles. These findings are given within the framework of the investigation (in proportion to the increase in porosity). The study concluded that when permeability declined, the angular dependence of frequency-dependent attenuation reduced, resulting in iso-porous curves. The study also discovered that the matrix porosity largely affected the angular dependency of the viscous losses in the range of 1.4 × 10−14 m2 permeability. Full article
(This article belongs to the Special Issue Recent Advances in Artificial Intelligence Applications in Radio Propagation for Communications)
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