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5G/6G Networks for Wireless Communication and IoT—2nd Edition
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5G/6G Networks for Wireless Communication and IoT—2nd Edition

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

Deadline for manuscript submissions: 31 January 2027 | Viewed by 3000

Editors

Prof. Dr. Giuseppe Araniti

E-Mail Website
Guest Editor
Department of Information Engineering, Infrastructure and Sustainable Energy (DIIES), University Mediterranea of Reggio Calabria, 89122 Reggio Calabria, Italy
Interests: 5G; D2D; MTC/M2M; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Dr. Chiara Suraci

E-Mail Website
Guest Editor
DIIES Department, University Mediterranea of Reggio Calabria, 89122 Reggio Calabria, Italy
Interests: 5G; eHealth; virtualization; network security; D2D
Special Issues, Collections and Topics in MDPI journals
Dr. Antonino Orsino

E-Mail Website
Guest Editor
Ericsson Research, Hirsalantie 11, 02420 Jorvas, Finland
Interests: 5G; mmWave; sidelink; Internet of Things; D2D
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the first edition of our Special Issue entitled “5G/6G Networks for Wireless Communication and IoT”, we again invite our international colleagues to contribute their expertise, insight, and findings in the form of original research articles and reviews to its second edition.

Although fifth-generation (5G) networks are still in the deployment phase, researchers are already investigating the upcoming sixth-generation (6G). It is generally agreed that the requirements of future wireless networks will be primarily determined by the applications they will have to support. Therefore, it is crucial to conduct thorough research and analysis on the technologies most suitable to ensure the key requirements of 6G networks and to understand what the characteristics of the 6G should be in order to bring more benefits compared to previous generations.

As for the potential use cases of 6G networks, the Internet of Things (IoT) has recently received great attention and is set to take a leading role in the future. Smart devices that exploit connectivity offered by mobile wireless networks are currently deployed everywhere and impact various contexts, so adapting the IoT to new concepts, such as the Internet of Everything (IoE), the Internet of Medical Things (IoMT), and the Artificial Intelligence of Things (AIoT), is extremely important.

The purpose of this Special Issue is to gather insights on the main characteristics and technologies that 5G/6G networks must embed to meet the requirements of legacy and modern IoT-related applications for their proliferation in the near future.

This Special Issue will cover, but is not limited to, the following topics:

  • Requirements, use cases, and enabling technologies of future 6G networks;
  • Evolution of wireless networks from 5G to 6G;
  • Measurement frameworks for 5G/6G;
  • The role of cloud computing in 6G networks application;
  • Edge computing for context-awareness in 6G-oriented IoT applications;
  • Spectrum sharing in beyond 5G networks;
  • Terahertz communications;
  • Programmable and virtualized networks for 5G/6G;
  • Group communications in 5G/6G;
  • Energy efficiency in 5G/6G-enabled IoT networks;
  • Machine learning/artificial intelligence for network management in 5G/6G networks;
  • Non-terrestrial network-aided communications in 6G;
  • The IoE paradigm as an evolution of the IoT;
  • Wearable IoT devices in future applications;
  • The evolution of security protection mechanisms in cellular networks;
  • Trust, security, and privacy in 6G and IoT.

Prof. Dr. Giuseppe Araniti
Dr. Chiara Suraci
Dr. Antonino Orsino
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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.

Publisher’s Notice

At the request of Dr. Roberto Morabito, a member of the original Guest Editor team for the Special Issue “5G/6G Networks for Wireless Communication and IoT—2nd Edition”, he will no longer be involved in the editorial handling of the Special Issue as of 2 June 2026. This change has been agreed upon by the remaining Guest Editors and the Editorial Office, and the Special Issue website has been updated accordingly. The Special Issue will continue to be handled by the remaining Guest Editors in accordance with MDPI’s Special Issue and editorial policies.

Keywords

  • 6G
  • wireless communications
  • IoT
  • future applications
  • network security and privacy

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (4 papers)

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Research

23 pages, 4046 KB  
Article
Experimental Validation of a Distributed 5G Core with Store-and-Forward for IoT Sensing over LEO Non-Terrestrial Networks
by Victor Monzon Baeza, Francesc Xavier Romero Soto, Raúl Parada and Carlos Monzo
Sensors 2026, 26(15), 4919; https://doi.org/10.3390/s26154919 - 4 Aug 2026
Viewed by 256
Abstract
Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) are emerging as a promising connectivity solution for Internet of Things (IoT) sensing applications deployed in remote, isolated, or infrastructure-limited environments. However, sparse LEO constellations inherently lead to intermittent connectivity, long service gaps, and frequent disruptions, [...] Read more.
Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) are emerging as a promising connectivity solution for Internet of Things (IoT) sensing applications deployed in remote, isolated, or infrastructure-limited environments. However, sparse LEO constellations inherently lead to intermittent connectivity, long service gaps, and frequent disruptions, challenging conventional 5G architectures that assume continuous end-to-end availability. This paper presents and experimentally validates a distributed 5G Core architecture enhanced with Store-and-Forward (S&F) capabilities to enable reliable delivery of IoT sensing data over intermittently connected LEO-NTN scenarios. The proposed architecture distributes selected 5G Core functions between ground and satellite nodes and introduces an S&F module capable of locally buffering uplink IoT data during periods without feeder-link connectivity and forwarding them once the ground connection is restored. A functional prototype is implemented using Open5GS, UERANSIM, and an emulated satellite node, and experimentally evaluated under representative intermittent-connectivity conditions. The results demonstrate that the proposed architecture successfully preserves and delivers IoT sensing data across temporary link disruptions. The experimental findings confirm the feasibility of integrating S&F mechanisms into distributed 5G Core architectures and provide practical insights into the design of resilient IoT sensing services over sparse LEO constellations. Full article
(This article belongs to the Special Issue 5G/6G Networks for Wireless Communication and IoT—2nd Edition)
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24 pages, 1226 KB  
Article
Generative Adversarial Network-Based Joint Mapping and Localization for Millimeter-Wave Communication Systems
by Zexu Zhao, Zhigang Chen and Lu Chen
Sensors 2026, 26(13), 4319; https://doi.org/10.3390/s26134319 - 7 Jul 2026
Viewed by 311
Abstract
In this paper, we propose a novel generative adversarial network (GAN)-based joint localization and mapping (JLAM) method using angle difference of arrival (ADOA) measurements for millimeter-wave (mmWave) communication systems. The proposed method adopts a deep auto-encoder neural network as the discriminator of the [...] Read more.
In this paper, we propose a novel generative adversarial network (GAN)-based joint localization and mapping (JLAM) method using angle difference of arrival (ADOA) measurements for millimeter-wave (mmWave) communication systems. The proposed method adopts a deep auto-encoder neural network as the discriminator of the GAN and models the generator as an explicit geometric ADOA function of the access point (AP) positions and the mobile terminal (MT) position, rather than as a conventional black-box neural network. By exploiting the two-dimensional distribution characteristics of high-dimensional ADOA vectors collected at a large number of random and unknown MT positions, the proposed method learns the ADOA data distribution and transforms it into the AP geometric topology. Then, the MT positions and the indoor map are estimated based on the recovered physical and virtual AP topology. The simulation results show that, under the representative setting with N=2000 measured ADOA vectors and σ=2° AOA measurement noise, the proposed method achieves an average localization error of about 0.25 m, compared with about 0.60 m for the JADE algorithm, corresponding to an error reduction of approximately 58%. The proposed method also provides more accurate room boundary estimation than JADE, confirming its effectiveness for mmWave JLAM. Full article
(This article belongs to the Special Issue 5G/6G Networks for Wireless Communication and IoT—2nd Edition)
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19 pages, 675 KB  
Article
MEC-Enabled Hierarchical Federated Learning for Resource-Aware Device Selection in IIoT
by Hu Tao, Duan Li, Bin Qiu and Shihua Liang
Sensors 2026, 26(4), 1380; https://doi.org/10.3390/s26041380 - 22 Feb 2026
Viewed by 705
Abstract
Hierarchical federated learning (HFL) combined with the Mobile Edge Computing (MEC) paradigm has attracted extensive research interest in the Industrial Internet of Things (IIoT) due to its ability to deploy computational resources near edge devices and effectively reduce communication overhead. However, in real-world [...] Read more.
Hierarchical federated learning (HFL) combined with the Mobile Edge Computing (MEC) paradigm has attracted extensive research interest in the Industrial Internet of Things (IIoT) due to its ability to deploy computational resources near edge devices and effectively reduce communication overhead. However, in real-world applications, the dynamic participation of edge devices and their diverse training objectives can lead to instability in model convergence, affecting overall system performance. To address this challenge, this paper proposes a device selection strategy based on task completion probability to determine participating devices dynamically in each training round. Furthermore, to balance system resource consumption and model performance, we formulate an optimization objective to minimize the loss function under resource constraints. By leveraging theoretical analysis, we reformulate the objective as a loss upper bound minimization problem related to resource allocation, which is subsequently decomposed into multiple subproblems for iterative solving. Simulation results demonstrate that the proposed method achieves superior resource efficiency and training stability. Compared to the state-of-the-art HFL method, DSRA-HFL reduces the average training delay by approximately 18% and energy consumption by 22% under dynamic conditions, while maintaining a competitive model accuracy. This validates the effectiveness of our joint optimization strategy in practical IIoT scenarios. Full article
(This article belongs to the Special Issue 5G/6G Networks for Wireless Communication and IoT—2nd Edition)
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18 pages, 714 KB  
Article
LoRa-Based IoT Multi-Hop Architecture for Smart Vineyard Monitoring: Simulation Framework and System Design
by Chiara Suraci, Pietro Zema, Giuseppe Marrara, Angelo Tropeano, Alessandro Campolo, Mariateresa Russo and Giuseppe Araniti
Sensors 2026, 26(4), 1112; https://doi.org/10.3390/s26041112 - 9 Feb 2026
Cited by 1 | Viewed by 1104
Abstract
The growing interest in precision agriculture has led, in recent years, to an increase in the adoption of Internet of Things (IoT) technologies in the service of smart agriculture to optimize agricultural production processes through the monitoring of environmental conditions and prevent food [...] Read more.
The growing interest in precision agriculture has led, in recent years, to an increase in the adoption of Internet of Things (IoT) technologies in the service of smart agriculture to optimize agricultural production processes through the monitoring of environmental conditions and prevent food loss. This work stems from research conducted as part of the Tech4You project, where the enabling digital technologies developed in Spoke 6 contribute to the advanced solutions envisaged by Spoke 3 to facilitate the transition to a sustainable agrifood system. In particular, we present the design and evaluation of a multi-hop Device-to-Device (D2D) communication architecture that leverages Long Range (LoRa) technology, specifically designed for monitoring vineyards in the context of passito wine production. The proposed framework addresses the challenge of monitoring mobile containers for grapes during the drying phase, a critical stage in which inadequate temperatures and humidity can promote the growth of fungi and the formation of mycotoxins. The integration of simulation-based performance evaluation with a multi-layer system architecture is presented in this work. The objective is to compare the performance of different routing strategies in choosing data forwarding paths to the gateway. The simulation results show that the proposed routing strategy, which is based on learning but also focuses on energy consumption, offers good performance. In particular, it achieves packet delivery rates of over 92% and preserves over 95% of active nodes after 2 h of operation. Energy-aware routing strategies also perform well compared to those that only consider the distance from the destination, but overall, the proposed strategy achieves a better trade-off on the metrics analyzed. Full article
(This article belongs to the Special Issue 5G/6G Networks for Wireless Communication and IoT—2nd Edition)
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