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Electronics
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5G Technology for Internet of Things Applications
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5G Technology for Internet of Things Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 May 2026 | Viewed by 1578

Special Issue Editor

Dr. Mohammed Amine Togou

E-Mail Website
Guest Editor
School of Computing, Dublin City University, D09 Y074 Dublin, Ireland
Interests: 5G networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent years have seen a significant surge in the number of Internet of Things (IoT) applications and services across different industry verticals, including healthcare, manufacturing, and automotive. These applications have different requirements, e.g., bandwidth, latency, reliability, and energy, that the current mobile networks cannot fully accommodate given the way in which they are built and operated. Fifth-generation technology represents an auspicious solution to the ever-growing user demands as it endorses a new architecture, called Open-RAN (O-RAN), that provides flexible and programmable network infrastructure that can be tailored to the specific needs of every application. It also implements Artificial Intelligence (AI) and Machine Learning (ML) techniques across different layers, i.e., Radio Access Network (RAN) and Core, to enhance network management and energy efficiency. Although efforts have lately been devoted to study and enhance the performance of the O-RAN architecture, several open issues need to be addressed, including service and resource management, energy consumption, security, and standardisation. As a result, this Special Issue aims to provide a comprehensive overview of theoretical and experimental research to help shape the future development and deployment of Open RAN-enabled IoT systems. Prospective authors are invited to submit original contributions in areas including, but not limited to, the following:

  • Novel 5G-enabled IoT frameworks;
  • O-RAN deployments for IoT use cases and applications;
  • Discovery algorithms of devices and services in 5G-enabled IoT systems;
  • Device search algorithms for 5G-enabled IoT systems;
  • Blockchain-enabled 5G-based IoT systems;
  • Intelligent devices for 5G security;
  • Optimisation algorithms for O-RAN resource allocation;
  • Interference mitigation algorithms for O-RAN;
  • Machine learning techniques for efficient energy consumption in 5G-enabled IoT systems;
  • RAN intelligent controllers;
  • Design, implementation, and evaluation of xApps, rApps, and dApps for O-RAN;
  • Machine learning techniques to enhance O-RAN security;
  • Conflict mitigation in O-RAN networks;
  • O-RAN testbeds and trials;
  • IoT in the 6th generation.

Dr. Mohammed Amine Togou
Guest Editor

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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics 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 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

  • 5th generation cellular communications
  • Internet of Things
  • open-RAN
  • intelligent devices
  • performance optimisation
  • energy efficiency

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Published Papers (2 papers)

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Research

22 pages, 10664 KB  
Article
Performance Enhancement of Low-Altitude Intelligent Network Communications Using Spherical-Cap Reflective Intelligent Surfaces
by Hengyi Sun, Xingcan Feng, Weili Guo, Xiaochen Zhang, Yuze Zeng, Guoshen Tan, Yong Tan, Changjiang Sun, Xiaoping Lu and Liang Yu
Electronics 2025, 14(24), 4848; https://doi.org/10.3390/electronics14244848 - 9 Dec 2025
Viewed by 532
Abstract
Unmanned Aerial Vehicles (UAVs) are integral components of future 6G networks, offering rapid deployment, enhanced line-of-sight communication, and flexible coverage extension. However, UAV communications in low-altitude environments face significant challenges, including rapid link variations due to attitude instability, severe signal blockage by urban [...] Read more.
Unmanned Aerial Vehicles (UAVs) are integral components of future 6G networks, offering rapid deployment, enhanced line-of-sight communication, and flexible coverage extension. However, UAV communications in low-altitude environments face significant challenges, including rapid link variations due to attitude instability, severe signal blockage by urban obstacles, and critical sensitivity to transmitter–receiver alignment. While traditional planar reconfigurable intelligent surfaces (RIS) show promise for mitigating these issues, they exhibit inherent limitations such as angular sensitivity and beam squint in wideband scenarios, compromising reliability in dynamic UAV scenarios. To address these shortcomings, this paper proposes and evaluates a spherical-cap reflective intelligent surface (ScRIS) specifically designed for dynamic low-altitude communications. The intrinsic curvature of the ScRIS enables omnidirectional reflection capabilities, significantly reducing sensitivity to UAV attitude variations. A rigorous analytical model founded on Generalized Sheet Transition Conditions (GSTCs) is developed to characterize the electromagnetic scattering of the curved metasurface. Three distinct 1-bit RIS unit cell coding arrangements, namely alternate, chessboard, and random, are investigated via numerical simulations utilizing CST Microwave Studio and experimental validation within a mechanically stirred reverberation chamber. Our results demonstrate that all tested ScRIS coding patterns markedly enhance electromagnetic field uniformity within the chamber and reduce the lowest usable frequency (LUF) by approximately 20% compared to a conventional metallic spherical reflector. Notably, the random coding pattern maximizes phase entropy, achieves the most uniform scattering characteristics and substantially reduces spatial field autocorrelation. Furthermore, the combined curvature and coding functionality of the ScRIS facilitates simultaneous directional focusing and diffuse scattering, thereby improving multipath diversity and spatial coverage uniformity. This effectively mitigates communication blind spots commonly encountered in UAV applications, providing a resilient link environment despite UAV orientation changes. To validate these findings in a practical context, we conduct link-level simulations based on a reproducible system model at 3.5 GHz, utilizing electromagnetic scale invariance to bridge the fundamental scattering properties observed in the RC to the application band. The results confirm that the ScRIS architecture can enhance link throughput by nearly five-fold at a 10 km range compared to a baseline scenario without RIS. We also propose a practical deployment strategy for urban blind-spot compensation, discuss hybrid planar-curved architectures, and conduct an in-depth analysis of a DRL-based adaptive control framework with explicit convergence and complexity analysis. Our findings validate the significant potential of ScRIS as a passive, energy-efficient solution for enhancing communication stability and coverage in multi-band 6G networks. Full article
(This article belongs to the Special Issue 5G Technology for Internet of Things Applications)
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23 pages, 2131 KB  
Article
Communication Base Station Site Selection Method Based on an Improved Genetic Algorithm
by Jinxuan Li, Hongyan Wang, Shengliang Fang, Youchen Fan and Shuya Zhang
Electronics 2025, 14(20), 3977; https://doi.org/10.3390/electronics14203977 - 10 Oct 2025
Viewed by 719
Abstract
With the large-scale deployment of 5G technology, the rationality of communication base station siting is crucial for network performance, construction costs, and operational efficiency. Traditional site selection methods rely heavily on manual experience, exhibiting strong subjectivity and difficulty in balancing multi-objective optimization. Existing [...] Read more.
With the large-scale deployment of 5G technology, the rationality of communication base station siting is crucial for network performance, construction costs, and operational efficiency. Traditional site selection methods rely heavily on manual experience, exhibiting strong subjectivity and difficulty in balancing multi-objective optimization. Existing heuristic algorithms suffer from slow convergence speeds and susceptibility to local optima. To address these challenges, this paper constructs a multi-objective base station site selection model that simultaneously minimizes costs, maximizes coverage contributions, and minimizes interference. It achieves quantitative balance among objectives through normalization and weight fusion, while introducing constraints to ensure engineering feasibility. Concurrently, the genetic algorithm underwent targeted optimization by introducing an adaptive migration strategy based on population diversity and a cosine-type parameter adjustment strategy. This approach was integrated with the particle swarm optimization algorithm to balance exploration and exploitation while mitigating premature convergence. Experimental validation demonstrates that the improved algorithm achieves faster convergence and greater stability compared to traditional genetic algorithms and particle swarm optimization, while satisfying engineering constraints such as base station quantity, coverage, and interference. This research provides an efficient and feasible solution for intelligent base station site planning. Full article
(This article belongs to the Special Issue 5G Technology for Internet of Things Applications)
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