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Technologies
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Intelligent Reflecting Surfaces for 5G and Beyond
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Intelligent Reflecting Surfaces for 5G and Beyond

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 15248

Special Issue Editors

Prof. Dr. Sotirios K. Goudos

E-Mail Website
Guest Editor
Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: antenna design; microwave components design; wireless communications; evolutionary algorithms; machine learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Shaohua Wan

E-Mail Website
Guest Editor
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China
Interests: Internet of Things (IoT); edge computing; machine learning; computer vision; cyber physical systems; future Internet architecture and smart-energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRS) are an emerging transmission technology for application to wireless communications. They can reconfigure the wireless propagation environment via software-control reflection. Following the recent breakthrough on the fabrication of programmable metamaterials, reconfigurable intelligent surfaces have the potential to fulfill the challenging vision for 6G networks and materialize seamless connections and intelligent software-based control of the environment in wireless communication systems. Since IRS reflection beamforming prediction requires the perfect/imperfect channel knowledge, channel estimation is a crucial aspect for predicting IRS interaction matrices. In this context, IRS is combined with machine learning (ML) techniques, which are particularly powerful in providing channel estimation. This Special Issue aims at publishing high-quality research papers as well as review articles addressing recent advances on IRS-aided wireless communications for 5G and beyond. Potential topics include but are not limited to the following:

  • IRS antenna design;
  • IRS channel modeling;
  • IRS channel capacity and performance limits;
  • IRS and ML techniques;
  • IRS channel estimation and channel feedback;
  • IRS indoor channel characterization;
  • IRS and NOMA techniques;
  • IRS prototyping and experimental results;
  • Cross-layer design for IRS-aided communications;
  • IRS and wireless power transfer communication;
  • IRS and mobile edge computing systems;
  • IRS and physical layer security techniques;
  • IRS and vehicle communications;
  • IRS transmissive and hybrid.

Dr. Sotirios K. Goudos
Prof. Dr. Shaohua Wan
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. Technologies 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 1600 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

  • intelligent reflecting surfaces
  • reconfigurable intelligent surfaces
  • 5G
  • 6G
  • machine learning

Published Papers (4 papers)

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Research

22 pages, 2712 KiB  
Article
An Exposimetric Electromagnetic Comparison of Mobile Phone Emissions: 5G versus 4G Signals Analyses by Means of Statistics and Convolutional Neural Networks Classification
by Simona Miclaus, Delia B. Deaconescu, David Vatamanu and Andreea M. Buda
Technologies 2023, 11(5), 113; https://doi.org/10.3390/technologies11050113 - 24 Aug 2023
Cited by 1 | Viewed by 3029
Abstract
To gain a deeper understanding of the hotly contested topic of the non-thermal biological effects of microwaves, new metrics and methodologies need to be adopted. The direction proposed in the current work, which includes peak exposure analysis and not just time-averaged analysis, aligns [...] Read more.
To gain a deeper understanding of the hotly contested topic of the non-thermal biological effects of microwaves, new metrics and methodologies need to be adopted. The direction proposed in the current work, which includes peak exposure analysis and not just time-averaged analysis, aligns well with this objective. The proposed methodology is not intended to facilitate a comparison of the general characteristics between 4G and 5G mobile communication signals. Instead, its purpose is to provide a means for analyzing specific real-life exposure conditions that may vary based on multiple parameters. A differentiation based on amplitude-time features of the 4G versus 5G signals is followed, with the aim of describing the peculiarities of a user’s exposure when he runs four types of mobile applications on his mobile phone on either of the two mobile networks. To achieve the goals, we used signal and spectrum analyzers with adequate real-time analysis bandwidths and statistical descriptions provided by the amplitude probability density (APD) function, the complementary cumulative distribution function (CCDF), channel power measurements, and recorded spectrogram databases. We compared the exposimetric descriptors of emissions specific to file download, file upload, Internet video streaming, and video call usage in both 4G and 5G networks based on the specific modulation and coding schemes. The highest and lowest electric field strengths measured in the air at a 10 cm distance from the phone during emissions are indicated. The power distribution functions with the highest prevalence are highlighted and commented on. Afterwards, the capability of a convolutional neural network that belongs to the family of single-shot detectors is proven to recognize and classify the emissions with a very high degree of accuracy, enabling traceability of the dynamics of human exposure. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G and Beyond)
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18 pages, 13150 KiB  
Article
Challenges of Using the L-Band and S-Band for Direct-to-Cellular Satellite 5G-6G NTN Systems
by Alexander Pastukh, Valery Tikhvinskiy, Svetlana Dymkova and Oleg Varlamov
Technologies 2023, 11(4), 110; https://doi.org/10.3390/technologies11040110 - 10 Aug 2023
Cited by 11 | Viewed by 5111
Abstract
This article presents a comprehensive study of the potential utilization of the L-band and S-band frequency ranges for satellite non-terrestrial network (NTN) technologies. This study encompasses an interference analysis in the S-band, investigating the coexistence of NTN satellite systems with mobile satellite networks [...] Read more.
This article presents a comprehensive study of the potential utilization of the L-band and S-band frequency ranges for satellite non-terrestrial network (NTN) technologies. This study encompasses an interference analysis in the S-band, investigating the coexistence of NTN satellite systems with mobile satellite networks such as Omnispace and Lyra, and an interference analysis in the L-band between NTN satellites and the mobile satellite network Inmarsat. This study simulates an NTN satellite network with typical characteristics defined by 3GPP and ITU-R for the n255 and n256 bands. Furthermore, it provides calculations illustrating the signal-to-noise ratio degradation of low-Earth-orbit (LEO), medium-Earth-orbit (MEO), and geostationary-Earth-orbit (GEO) satellite networks operating in the L-band and S-band when exposed to interference from NTN satellites. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G and Beyond)
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13 pages, 1635 KiB  
Article
Cross-Tier Interference Mitigation for RIS-Assisted Heterogeneous Networks
by Abdel Nasser Soumana Hamadou, Ciira wa Maina and Moussa Moindze Soidridine
Technologies 2023, 11(3), 73; https://doi.org/10.3390/technologies11030073 - 09 Jun 2023
Viewed by 2673
Abstract
With the development of the next generation of mobile networks, new research challenges have emerged, and new technologies have been proposed to address them. On the other hand, reconfigurable intelligent surface (RIS) technology is being investigated for partially controlling wireless channels. RIS is [...] Read more.
With the development of the next generation of mobile networks, new research challenges have emerged, and new technologies have been proposed to address them. On the other hand, reconfigurable intelligent surface (RIS) technology is being investigated for partially controlling wireless channels. RIS is a promising technology for improving signal quality by controlling the scattering of electromagnetic waves in a nearly passive manner. Heterogeneous networks (HetNets) are another promising technology that is designed to meet the capacity requirements of the network. RIS technology can be used to improve system performance in the context of HetNets. This study investigates the applications of reconfigurable intelligent surfaces (RISs) in heterogeneous downlink networks (HetNets). Due to the network densification, the small cell base station (SBS) interferes with the macrocell users (MUEs). In this paper, we utilise RIS to mitigate cross-tier interference in a HetNet via directional beamforming by adjusting the phase shift of the RIS. We consider RIS-assisted heterogeneous networks consisting of multiple SBS nodes and MUEs that utilise both direct paths and reflected paths. Therefore, the aim of this study is to maximise the sum rate of all MUEs by jointly optimising the transmit beamforming of the macrocell base station (MBS) and the phase shift of the RIS. An efficient RIS reflecting coefficient-based optimisation (RCO) is proposed based on a successive convex approximation approach. Simulation results are provided to show the effectiveness of the proposed scheme in terms of its sum rate in comparison with the scheme HetNet without RIS and the scheme HetNet with RIS but with random phase shifts. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G and Beyond)
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15 pages, 14241 KiB  
Article
Dual-Band Rectifier Circuit Design for IoT Communication in 5G Systems
by Ioannis D. Bougas, Maria S. Papadopoulou, Achilles D. Boursianis, Spyridon Nikolaidis and Sotirios K. Goudos
Technologies 2023, 11(2), 34; https://doi.org/10.3390/technologies11020034 - 24 Feb 2023
Cited by 2 | Viewed by 2108
Abstract
Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More [...] Read more.
Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More particularly, we designed a dual-band RF to DC rectifier circuit at sub-6 GHz in the 5G bands, able to supply low-power sensors and microcontrollers used in agriculture, the military, or health services. The system operates at 3.5 GHz and 5 GHz in the 5G cellular network’s frequency band FR1. Numerical results reveal that the system provides maximum power conversion efficiency (PCE) equal to 53% when the output load (sensor or microcontroller) is 1.74 kΩ and the input power is 12 dBm. Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G and Beyond)
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