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IoT
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Advances in Wireless Communication Technologies for IoT Devices
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Advances in Wireless Communication Technologies for IoT Devices

A special issue of IoT (ISSN 2624-831X).

Deadline for manuscript submissions: 30 May 2026 | Viewed by 1166

Special Issue Editors

Dr. Long Zhao

E-Mail Website
Guest Editor
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: wireless communications; signal processing; artificial intelligence
Dr. Rui Chen

E-Mail Website
Guest Editor
School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
Interests: wireless communications; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals
Dr. Jie Mei

E-Mail Website
Guest Editor
College of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
Interests: Internet of Vehicles; Internet of Things

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is rapidly expanding, with tens of billions of connected devices projected to shape our future smart cities, industries, homes, and environment. This exponential growth presents unprecedented challenges for wireless communication technologies, demanding low-power, wide-ranging, high-capacity, low-cost, and highly reliable solutions. No single technology can satisfy all these diverse requirements, leading to a dynamic ecosystem of complementary and converging innovations.

This Special Issue aims to provide cutting-edge research and review articles that address the latest advancements, challenges, and future trajectories in wireless technologies tailored for IoT applications. We seek to explore the entire spectrum, from long-range cellular and satellite solutions that connect remote assets to ultra-low-power backscatter communication for battery-less sensors, and the integration challenges within complex environments such as smart homes. The goal is to foster discussion on how these technologies can coexist, interoperate, and evolve to create a truly seamless and sustainable connected world.

We welcome the submission of high-quality original research articles and comprehensive review papers that align with, but are not limited to, the following themes:

  • 5G-advanced/future 6G for cellular IoT.
  • Next-generation LPWAN for optimized cost, coverage, and power consumption.
  • Satellite IoT or non-terrestrial networks for IoT.
  • Ambient backscatter and battery-free systems for IoT.
  • AI/ML-driven wireless resource management for IoT.
  • Advanced short-range networking for IoT.
  • Joint communication and sensing (JCAS) for IoT.
  • Security and privacy for constrained devices.
  • Network slicing and edge intelligence for IoT.

Dr. Long Zhao
Dr. Rui Chen
Dr. Jie Mei
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. IoT is an international peer-reviewed open access quarterly 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 1400 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

  • IoT
  • cellular
  • short-range networking
  • satellite
  • communication
  • sensing
  • AI

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

Published Papers (2 papers)

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19 pages, 407 KB  
Article
An IoT-Aware Certificateless Signature Scheme for Protection Against Type-I and Type-II Super Adversaries
by Parichehr Dadkhah, Parvin Rastegari, Mohammad Dakhilalian, Phil Yeoh, Mingzhong Wang, Shahrzad Saremi and Rania Shibl
IoT 2026, 7(2), 40; https://doi.org/10.3390/iot7020040 - 7 May 2026
Viewed by 119
Abstract
Internet of Things (IoT) assists in efficient connectivity and automation of various applications by making use of wireless communication technology. Ensuring secure authentication and data integrity are the main challenges in this open wireless platform. Although existing cryptographic methods can address these security [...] Read more.
Internet of Things (IoT) assists in efficient connectivity and automation of various applications by making use of wireless communication technology. Ensuring secure authentication and data integrity are the main challenges in this open wireless platform. Although existing cryptographic methods can address these security challenges, most of them incur additional computational and communication overhead, which is unsuitable for resource-constrained IoT devices. Nowadays, researchers have focused on proposing efficient schemes to satisfy security requirements in open wireless IoT frameworks. Recently, a Certificateless Signature (CLS) scheme was developed for the IoT environment. However, in this paper, we show that this CLS scheme is vulnerable to attacks by super Type-II adversaries. To strengthen this scheme, we propose a novel and efficient CLS scheme with existential unforgeability against super adversaries in the Random Oracle Model (ROM). The proposed CLS scheme achieves reduced computational complexity and communication cost. As such, it is suitable for wireless IoT networks to provide secure message authentication and data integrity. Full article
(This article belongs to the Special Issue Advances in Wireless Communication Technologies for IoT Devices)
22 pages, 4808 KB  
Article
Transforming Opportunistic Routing: A Deep Reinforcement Learning Framework for Reliable and Energy-Efficient Communication in Mobile Cognitive Radio Sensor Networks
by Suleiman Zubair, Bala Alhaji Salihu, Altyeb Altaher Taha, Yakubu Suleiman Baguda, Ahmed Hamza Osman and Asif Hassan Syed
IoT 2026, 7(2), 34; https://doi.org/10.3390/iot7020034 - 21 Apr 2026
Viewed by 329
Abstract
The Mobile Reliable Opportunistic Routing (MROR) protocol improves data-forwarding reliability in Cognitive Radio Sensor Networks (CRSNs) through mobility-aware virtual contention groups and handover zoning. However, its heuristic decision logic is difficult to optimize under highly dynamic spectrum access and random node mobility. To [...] Read more.
The Mobile Reliable Opportunistic Routing (MROR) protocol improves data-forwarding reliability in Cognitive Radio Sensor Networks (CRSNs) through mobility-aware virtual contention groups and handover zoning. However, its heuristic decision logic is difficult to optimize under highly dynamic spectrum access and random node mobility. To address this limitation, we present DRL-MROR, a refined routing framework that incorporates deep reinforcement learning (DRL) to enable intelligent and adaptive forwarding decisions. In DRL-MROR, the secondary users (SUs) act as autonomous agents that observe local state information, including primary-user activity, link quality, residual energy, and neighbor-mobility patterns. Each agent learns a forwarding policy through a Deep Q-Network (DQN) optimized for long-term network utility in terms of throughput, delay, and energy efficiency. We formulate routing as a Markov Decision Process (MDP) and use experience replay with prioritized sampling to improve learning stability and convergence. The DQN used at each node is intentionally lightweight, requiring 5514 trainable parameters, about 21.5 kB of weight storage in 32-bit precision, and approximately 5.4k multiply-accumulate operations per inference, which supports practical deployment on edge-capable CRSN nodes. Extensive simulations show that DRL-MROR outperforms the original MROR protocol and representative AI-based routing baselines such as AIRoute under diverse operating conditions. The results indicate gains of up to 38% in throughput, 42% in goodput, a 29% reduction in energy consumed per packet, and an approximately 18% improvement in network lifetime, while maintaining high route stability and fairness. DRL-MROR also reduces control overhead by about 30% and average end-to-end delay by up to 32%, maintaining strong performance even under elevated PU activity and higher node mobility. These results show that augmenting opportunistic routing with lightweight DRL can substantially improve adaptability and efficiency in next-generation IoT-oriented CRSNs. Full article
(This article belongs to the Special Issue Advances in Wireless Communication Technologies for IoT Devices)
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