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Advancing towards 6G Networks
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Advancing towards 6G Networks

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Communications and Networking".

Deadline for manuscript submissions: closed (25 December 2023) | Viewed by 13541

Special Issue Editors

Dr. Ayman Radwan

E-Mail Website
Guest Editor
Instituto de Telecomunicações and Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Interests: wireless communications; radio resource management; Internet of Things; future generations of mobile communications (5G)
Special Issues, Collections and Topics in MDPI journals
Dr. Maria de Fátima Domingues

E-Mail Website
Guest Editor
1. Department of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
2. Instituto de Telecomunicações, Aveiro, Portugal
Interests: optical fiber sensors; fiber Bragg gratings; Fabry-Perot interformetric sensors; eHealth applications; gait analysis; wearable sensing devices
Special Issues, Collections and Topics in MDPI journals
Dr. Abd-Elhamid Taha

E-Mail Website
Guest Editor
Electrical Engineering Program, Alfaisal University, Riyadh, Saudi Arabia
Interests: radio resource management; wireless networks; mobile computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The continuing deployment of 5G and 5G Advanced networks has impacted many sectors, and has supported the introduction and strengthening of many communication-based applications, especially in industrial automation, cloud-based services, and content distribution. In the process of 5G standardization, Release 18 will reach stages 2 and 3 in 2023, and early Release 19 studies are already underway.

Regarding applications, increased interest in mixed reality, digital twinning, and the metaverse has led to innovations that will be the cornerstones for realizing 6G networks. Advances in softwarization are also sought to better support increasing traffic and processing demands, especially in intelligent computation for IoT and smart cities.

This Special Issue seeks original, unpublished work targeting beyond-5G and 6G networks. We welcome propositions of new applications that focus on verticals, such as augmented and simulated realities, eHealth, smart cities, and intelligent transport.

This Special Issue welcomes work targeting network enhancement and optimization toward the wide adoption and improvement of the following applications and verticals.

  • Metaverse;
  • Digital twinning;
  • eHealth challenges and solutions;
  • Smart cities;
  • V2X communications;
  • Campus deployments;
  • 6G applications and services;
  • IoT challenges and solutions;
  • Energy-efficient networking;
  • AI and machine learning for 6G networking;
  • Network function virtualization;
  • Software-defined networks (SDN);
  • Fog and cloud solutions;
  • Mobile edge computing;
  • Mobility management;
  • Ultra-dense networking;
  • Cross-layer optimization.

Papers that consider other 6G verticals are also welcome.

Dr. Ayman Radwan
Dr. Maria de Fátima Domingues
Dr. Abd-Elhamid Taha
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. Journal of Sensor and Actuator Networks 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 2000 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.

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

Published Papers (4 papers)

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Research

24 pages, 1393 KiB  
Article
Network Sliced Distributed Learning-as-a-Service for Internet of Vehicles Applications in 6G Non-Terrestrial Network Scenarios
by David Naseh, Swapnil Sadashiv Shinde and Daniele Tarchi
J. Sens. Actuator Netw. 2024, 13(1), 14; https://doi.org/10.3390/jsan13010014 - 7 Feb 2024
Cited by 3 | Viewed by 2509
Abstract
In the rapidly evolving landscape of next-generation 6G systems, the integration of AI functions to orchestrate network resources and meet stringent user requirements is a key focus. Distributed Learning (DL), a promising set of techniques that shape the future of 6G communication systems, [...] Read more.
In the rapidly evolving landscape of next-generation 6G systems, the integration of AI functions to orchestrate network resources and meet stringent user requirements is a key focus. Distributed Learning (DL), a promising set of techniques that shape the future of 6G communication systems, plays a pivotal role. Vehicular applications, representing various services, are likely to benefit significantly from the advances of 6G technologies, enabling dynamic management infused with inherent intelligence. However, the deployment of various DL methods in traditional vehicular settings with specific demands and resource constraints poses challenges. The emergence of distributed computing and communication resources, such as the edge-cloud continuum and integrated terrestrial and non-terrestrial networks (T/NTN), provides a solution. Efficiently harnessing these resources and simultaneously implementing diverse DL methods becomes crucial, and Network Slicing (NS) emerges as a valuable tool. This study delves into the analysis of DL methods suitable for vehicular environments alongside NS. Subsequently, we present a framework to facilitate DL-as-a-Service (DLaaS) on a distributed networking platform, empowering the proactive deployment of DL algorithms. This approach allows for the effective management of heterogeneous services with varying requirements. The proposed framework is exemplified through a detailed case study in a vehicular integrated T/NTN with diverse service demands from specific regions. Performance analysis highlights the advantages of the DLaaS approach, focusing on flexibility, performance enhancement, added intelligence, and increased user satisfaction in the considered T/NTN vehicular scenario. Full article
(This article belongs to the Special Issue Advancing towards 6G Networks)
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17 pages, 1065 KiB  
Article
Echo State Learning for User Trajectory Prediction to Minimize Online Game Breaks in 6G Terahertz Networks
by Benedetta Picano, Leonardo Scommegna, Enrico Vicario and Romano Fantacci
J. Sens. Actuator Netw. 2023, 12(4), 58; https://doi.org/10.3390/jsan12040058 - 25 Jul 2023
Cited by 1 | Viewed by 1699
Abstract
Mobile online gaming is constantly growing in popularity and is expected to be one of the most important applications of upcoming sixth generation networks. Nevertheless, it remains challenging for game providers to support it, mainly due to its intrinsic and ever-stricter need for [...] Read more.
Mobile online gaming is constantly growing in popularity and is expected to be one of the most important applications of upcoming sixth generation networks. Nevertheless, it remains challenging for game providers to support it, mainly due to its intrinsic and ever-stricter need for service continuity in the presence of user mobility. In this regard, this paper proposes a machine learning strategy to forecast user channel conditions, aiming at guaranteeing a seamless service whenever a user is involved in a handover, i.e., moving from the coverage area of one base station towards another. In particular, the proposed channel condition prediction approach involves the exploitation of an echo state network, an efficient class of recurrent neural network, that is empowered with a genetic algorithm to perform parameter optimization. The echo state network is applied to improve user decisions regarding the selection of the serving base station, avoiding game breaks as much as possible to lower game lag time. The validity of the proposed framework is confirmed by simulations in comparison to the long short-term memory approach and another alternative method, aimed at thoroughly testing the accuracy of the learning module in forecasting user trajectories and in reducing game breaks or lag time, with a focus on a sixth generation network application scenario. Full article
(This article belongs to the Special Issue Advancing towards 6G Networks)
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18 pages, 4821 KiB  
Article
The Power of Data: How Traffic Demand and Data Analytics Are Driving Network Evolution toward 6G Systems
by Dario Sabella, Davide Micheli and Giovanni Nardini
J. Sens. Actuator Netw. 2023, 12(4), 49; https://doi.org/10.3390/jsan12040049 - 27 Jun 2023
Cited by 2 | Viewed by 4205
Abstract
The evolution of communication systems always follows data traffic evolution and further influences innovations that are unlocking new markets and services. While 5G deployment is still ongoing in various countries, data-driven considerations (extracted from forecasts at the macroscopic level, detailed analysis of live [...] Read more.
The evolution of communication systems always follows data traffic evolution and further influences innovations that are unlocking new markets and services. While 5G deployment is still ongoing in various countries, data-driven considerations (extracted from forecasts at the macroscopic level, detailed analysis of live network traffic patterns, and specific measures from terminals) can conveniently feed insights suitable for many purposes (B2B e.g., operator planning and network management; plus also B2C e.g., smarter applications and AI-aided services) in the view of future 6G systems. Moreover, technology trends from standards and research projects (such as Hexa-X) are moving with industry efforts on this evolution. This paper shows the importance of data-driven insights, by first exploring network evolution across the years from a data point of view, and then by using global traffic forecasts complemented by data traffic extractions from a live 5G operator network (statistical network counters and measures from terminals) to draw some considerations on the possible evolution toward 6G. It finally presents a concrete case study showing how data collected from the live network can be exploited to help the design of AI operations and feed QoS predictions. Full article
(This article belongs to the Special Issue Advancing towards 6G Networks)
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15 pages, 690 KiB  
Article
The Role of Optical Transport Networks in 6G and Beyond: A Vision and Call to Action
by Dimitrios Michael Manias, Abbas Javadtalab, Joe Naoum-Sawaya and Abdallah Shami
J. Sens. Actuator Netw. 2023, 12(3), 43; https://doi.org/10.3390/jsan12030043 - 22 May 2023
Cited by 6 | Viewed by 4116
Abstract
As next-generation networks begin to take shape, the necessity of Optical Transport Networks (OTNs) in helping achieve the performance requirements of future networks is evident. Future networks are characterized as being data-centric and are expected to have ubiquitous artificial intelligence integration and deployment. [...] Read more.
As next-generation networks begin to take shape, the necessity of Optical Transport Networks (OTNs) in helping achieve the performance requirements of future networks is evident. Future networks are characterized as being data-centric and are expected to have ubiquitous artificial intelligence integration and deployment. To this end, the efficient and timely transportation of fresh data from producer to consumer is critical. The work presented in this paper outlines the role of OTNs in future networking generations. Furthermore, key emerging OTN technologies are discussed. Additionally, the role intelligence will play in the Management and Orchestration (MANO) of next-generation OTNs is discussed. Moreover, a set of challenges and opportunities for innovation to guide the development of future OTNs is considered. Finally, a use case illustrating the impact of network dynamicity and demand uncertainty on OTN MANO decisions is presented. Full article
(This article belongs to the Special Issue Advancing towards 6G Networks)
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