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Future Internet
Special Issues
Intelligent Telecommunications Mobile Networks
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Intelligent Telecommunications Mobile Networks

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 2053

Special Issue Editors

Dr. Emanuele De Santis

E-Mail Website
Guest Editor
Department of Computer, Control and Management Engineering “Antonio Ruberti” (DIAG), Sapienza University of Rome—Via Ariosto, 25, 00185 Rome, Italy
Interests: control systems for 6G mobile telecommunication networks; control systems for power networks and smartgrids
Prof. Dr. Francesco Delli Priscoli

E-Mail Website
Guest Editor
Department of Computer, Control and Management Engineering “Antonio Ruberti” (DIAG), Sapienza University of Rome—Via Ariosto, 25, 00185 Rome, Italy
Interests: closed-loop multi-agent learning techniques; quality-of-experience management; decision support systems applied to various fields (healthcare systems, cellular systems, energy systems); critical infrastructures
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of mobile networks has ushered in a new era of connectivity that is having a profound impact on various facets of modern life, ranging from everyday communication to industrial automation. As we move closer to realizing the full potential of 5G and beyond, focus has increasingly shifted to smart telecoms networks that can meet the ever-increasing demand for speed, efficiency and reliability. These advanced networks are not just about faster data rates: they represent the convergence of cutting-edge technologies, including artificial intelligence, machine learning, smart caching and offloading, and edge computing, which together enable smarter, more responsive and adaptive mobile communications systems.

This Special Issue on “Intelligent Telecommunications Mobile Networks” is dedicated to exploring the innovative approaches and solutions driving the next generation of mobile networks. We invite submissions that address challenges and opportunities in the design, implementation, control and optimization of intelligent mobile networks. Topics of interest include, but are not limited to, AI-driven network management, intelligent spectrum sharing, edge intelligence, intelligent caching and offloading and the integration of IoT devices into mobile networks. Both theoretical contributions and practical implementations are welcome, as are comprehensive reviews and surveys that provide new insights into this rapidly evolving field.

We look forward to your valuable contributions to this Special Issue, which will push the boundaries of what is possible in the world of intelligent mobile telecommunications networks.

Dr. Emanuele De Santis
Prof. Dr. Francesco Delli Priscoli
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. Future Internet 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

  • B5G/6G communication systems
  • intelligent systems in telecommunication networks
  • sematic communication in mobile networks
  • intelligent caching and offloading
  • terrestrial/non-terrestrial networks convergence
  • AI-driven network management
  • machine learning in telecommunications
  • edge computing in mobile networks
  • adaptive spectrum sharing
  • 5G/6G network optimization
  • intelligent resource allocation
  • IoT integration in mobile networks
  • network slicing
  • cognitive radio networks
  • autonomous network operations
  • dynamic network topology
  • ultra-reliable low-latency communication (URLLC)
  • energy-efficient mobile networks
  • network function virtualization (NFV)
  • self-organizing networks (SONs)

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Published Papers (2 papers)

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Research

25 pages, 818 KiB  
Article
Emergency Messaging System for Urban Vehicular Networks Inspired by Social Insects’ Stigmergic Communication
by Ojilvie Avila-Cortés, Saúl E. Pomares Hernández, Julio César Pérez-Sansalvador and Lil María Xibai Rodríguez-Henríquez
Future Internet 2025, 17(3), 117; https://doi.org/10.3390/fi17030117 - 6 Mar 2025
Viewed by 373
Abstract
For occupant safety in vehicular networks, emergency messages derived from vehicular incidents should be exchanged only during their validity period and in zones containing involved entities. Problems arise for mobile entities in vehicular networks that change their location over time, where data may [...] Read more.
For occupant safety in vehicular networks, emergency messages derived from vehicular incidents should be exchanged only during their validity period and in zones containing involved entities. Problems arise for mobile entities in vehicular networks that change their location over time, where data may be further communicated in out-of-context space and time. Current solutions extend from the naive assumption of notifying every entity in the network about emergencies with data flooding and clusters and by means of specific communication only in the affected zones—geo-routing—of incidents’ relative data. However, delivering useless data to uninvolved entities results in wasted resources and more overheads in the former cases and the work of obtaining knowledge and secondary site services from neighbors in the latter. In this paper, we propose that the common task of disseminating emergency messages for occupant safety among entities should only be communicated only where and when useful, namely, if spatio-temporal constraints apply regarding those incidents. Our solution is inspired by the communication of working social insects that exchange data through pheromones regardless of closeness or knowledge among colony members for food retrieval. The results show that communication based on space–time constraints makes better use of resources than other solutions. Full article
(This article belongs to the Special Issue Intelligent Telecommunications Mobile Networks)
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14 pages, 1727 KiB  
Article
Machine Learning and Deep Learning-Based Multi-Attribute Physical-Layer Authentication for Spoofing Detection in LoRaWAN
by Azita Pourghasem, Raimund Kirner, Athanasios Tsokanos, Iosif Mporas and Alexios Mylonas
Future Internet 2025, 17(2), 68; https://doi.org/10.3390/fi17020068 - 6 Feb 2025
Viewed by 689
Abstract
The use of wireless sensor networks (WSNs) in critical applications such as environmental monitoring, smart agriculture, and industrial automation has created significant security concerns, particularly due to the broadcasting nature of wireless communication. The absence of physical-layer authentication mechanisms exposes these networks to [...] Read more.
The use of wireless sensor networks (WSNs) in critical applications such as environmental monitoring, smart agriculture, and industrial automation has created significant security concerns, particularly due to the broadcasting nature of wireless communication. The absence of physical-layer authentication mechanisms exposes these networks to threats like spoofing, compromising data authenticity. This paper introduces a multi-attribute physical layer authentication (PLA) scheme to enhance WSN security by using physical attributes such as received signal strength indicator (RSSI), battery level (BL), and altitude. The LoRaWAN join procedure, a key risk due to plain text transmission without encryption during initial communication, is addressed in this study. To evaluate the proposed approach, a partially synthesized dataset was developed. Real-world RSSI values were sourced from the LoRa at the Edge Dataset, while BL and altitude columns were added to simulate realistic sensor behavior in a forest fire detection scenario. Machine learning (ML) models, including Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbors (KNN), were compared with deep learning (DL) models, such as Multi-Layer Perceptron (MLP) and Convolutional Neural Networks (CNN). The results showed that RF achieved the highest accuracy among machine learning models, while MLP and CNN delivered competitive performance with higher resource demands. Full article
(This article belongs to the Special Issue Intelligent Telecommunications Mobile Networks)
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