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Future Horizons in Networking: Exploring the Potential of 6G
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Future Horizons in Networking: Exploring the Potential of 6G

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 519

Special Issue Editors

Dr. Arun Kumar

E-Mail Website
Guest Editor
Department of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela 769008, India
Interests: internet of things; wireless sensor networks; ad hoc and mobile networks; VANETs; communication algorithms
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Peter Han Joo Chong

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand
Interests: mobile computing; wireless communication systems and technologies; networking and communications; communications engineering; cyber–physical systems and the Internet of Things; 4/5/6G; vehicular networks; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advancement towards 6G networks marks remarkable progression in mobile communications. With the advent of 5G, we have witnessed unprecedented high data rates and remarkably low latencies, pushing the boundaries of what was once thought of as impossible. The key technologies for enhanced performance include mm-wave and THz spectrum communications, very large-scale antenna arrays (i.e., spatial modulation-MIMO), Artificial Intelligence (AI)/Machine Learning (ML), mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine type of communication (mMTC), etc. Now, the industry is poised to embark on its next transformative journey: the era of 6th Generation (6G) technologies. In addition, 6G is expected to integrate with AI, Internet of Things (IoTs), distributed computing, and other new technologies. However, like any nascent technology, it brings forth a distinct set of architectural demands, challenges, boundless prospects, and ample opportunities.

This Special Issue aims to put together high-quality research articles on recent advances in the theory and practical aspects related to 6G technologies to serve as valuable references and directions for researchers in this field, from the industry as well as academia. Topics may include, but are not limited to, the following:

  • Interoperability of 6G with 5G;
  • Performance analysis for 6G-enabled networks;
  • Low latency and high throughput features in 6G-based communication systems;
  • mm-wave and THz communications that power 6G communications;
  • Artificial Intelligence and deep learning applications in 6G-communication systems;
  • MIMO, eMBB, URLLC, and mMTC in 6G communication;
  • Energy efficient architectures and techniques for 6G;
  • Smart 6G networks enabled by network slicing;
  • Innovative edge cloud and IoT solutions enabled by 5G/6G technologies;
  • 6G services to improve user experience, efficiency, and costs;
  • Innovative services (e.g., Smart Cities, Autonomous Vehicles, IoT, Drones) enabled by AI and 6G;
  • Use of case studies on 6G services.

Dr. Arun Kumar
Prof. Dr. Peter Han Joo Chong
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. 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.

Keywords

  • 6G networks
  • Artificial Intelligence
  • Internet of Things

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Published Papers (2 papers)

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Research

30 pages, 8363 KiB  
Article
Integrating Reinforcement Learning into M/M/1/K Retry Queueing Models for 6G Applications
by Djamila Talbi and Zoltan Gal
Sensors 2025, 25(12), 3621; https://doi.org/10.3390/s25123621 - 9 Jun 2025
Abstract
The ever-growing demand for sustainable, efficient, and fair allocation in the next generation of wireless network applications is a serious challenge, especially in the context of high-speed communication networks that operate on Terahertz frequencies. This research work presents a novel approach to enhance [...] Read more.
The ever-growing demand for sustainable, efficient, and fair allocation in the next generation of wireless network applications is a serious challenge, especially in the context of high-speed communication networks that operate on Terahertz frequencies. This research work presents a novel approach to enhance queue management in 6G networks by integrating reinforcement learning, specifically Deep Q-Networks (DQN). We introduce an intelligent 6G Retrial Queueing System (RQS) that dynamically adjusts to varying traffic conditions, minimizes delays, reduces energy consumption, and guarantees equitable access to network resources. The system’s performance is examined under extensive simulations, taking into account multiple arrival rates, queue sizes, and reward scaling factors. The results show that the integration of RL in the 6G-RQS model successfully enhances queue management while maintaining the high performance of the system, and this is by increasing the number of mobile terminals served, even under different and higher traffic demands. Furthermore, singular value decomposition analysis reveals clusters and structured patterns, indicating the effective learning process and adaptation performed by the agent. Our research findings demonstrate that RL-based queue management is a promising solution for overcoming the challenges that 6G suffers from, particularly in the context of high-speed communication networks. Full article
(This article belongs to the Special Issue Future Horizons in Networking: Exploring the Potential of 6G)
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19 pages, 4740 KiB  
Article
Digital Twin Network-Based 6G Self-Evolution
by Yuhong Huang, Mancong Kang, Yanhong Zhu, Na Li, Guangyi Liu and Qixing Wang
Sensors 2025, 25(11), 3543; https://doi.org/10.3390/s25113543 - 4 Jun 2025
Viewed by 58
Abstract
Digital twins (DTs) will revolutionize network autonomy. Recent studies have promoted the idea of a DT-native 6G network, deeply integrating DTs into mobile network architectures to improve the timeliness of physical–digital synchronization and network optimizations. However, DTs have mainly acted just as a [...] Read more.
Digital twins (DTs) will revolutionize network autonomy. Recent studies have promoted the idea of a DT-native 6G network, deeply integrating DTs into mobile network architectures to improve the timeliness of physical–digital synchronization and network optimizations. However, DTs have mainly acted just as a tool for network autonomy, leading to a gap regarding the ultimate goal of network self-evolution. This paper analyzes future directions concerning DT-native networks. Specifically, the proposed architecture introduces a key concept called “future shots” that gives accurate network predictions under different time scales of self-evolution strategies for various network elements. To realize the future shots, we propose a long-term hierarchical convolutional graph attention model for cost-effective network predictions, a conditional hierarchical graph neural network for strategy generation, and methods for efficient small-to-large-scale interactions. The architecture is expected to facilitate high-level network autonomy for 6G networks. Full article
(This article belongs to the Special Issue Future Horizons in Networking: Exploring the Potential of 6G)
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