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Electronics
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Applications, Trends and Development for 5G/6G and beyond Wireless Communication...
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Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 10843

Special Issue Editors

Dr. Peng Yu

E-Mail Website
Guest Editor
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: 5G/6G network management and optimization; intelligent network control; green communication; smart grid communication
Special Issues, Collections and Topics in MDPI journals
Prof. Shuai Han

E-Mail Website
Guest Editor
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150080, China
Interests: wireless communications; physical layer technology and security; satellite communications and navigation
Special Issues, Collections and Topics in MDPI journals
Dr. Bo Rong

E-Mail Website
Guest Editor
Communications Research Centre, Ottawa, ON K2H 8S2, Canada
Interests: 5G; wireless communications; wireless networking; IoT; smart grid
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the commercialization of 5G networks, both academia and industry began to research and explore 6G and beyond wireless communication systems. Feature applications envisioned in the 6G era, represented by holographic communication, full-sensing communication, intelligent transportation, and intelligent manufacturing, place high demands on 6G networks. The aim of 6G is to provide the ultimate experience for all through hyper-connectivity involving humans and their surroundings, and these networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc.

To meet these requirements, 6G networks will rely on new enabling technologies. New air interface and transmission technologies are essential to achieve high spectrum efficiency and energy efficiency, including Terahertz communication, visible-light communication, new waveforms, multiple access approaches, channel coding methods, multi-antenna technologies, and proper combination of all these diversity techniques.

In the meantime, novel network architectures are needed, such as space–air–ground–sea-integrated communication networks, software-defined network/network functions virtualization (SDN/NFV), dynamic network slicing, service-based architecture, cognitive service architecture, cell-free architecture, and cloud/fog/edge-computing architectures.

In recent years, the rise of artificial intelligence (AI) has infiltrated various areas, and AI will usher in unprecedented paradigm shifts in 6G by providing native intelligence. Considering AI from the initial phase of developing concepts and technologies for 6G will give us more opportunities to take advantage of AI for improvement of overall network operation in terms of performance, cost, and the ability to provide various services.

However, the potential technologies and practical implementation of 6G networks are still in the very early stages, and many challenges have yet to be identified and resolved. This Special Issue aims to introduce and highlight the latest developments and emerging research in 6G and beyond wireless communication systems.

Dr. Peng Yu
Prof. Dr. Shuai Han
Dr. Bo Rong
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. 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

  • 6G air interface technologies
  • 6G transmission technologies
  • 6G network technologies
  • Artificial intelligence for 6G networks

Published Papers (6 papers)

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Research

16 pages, 2888 KiB  
Article
Machine Learning with Adaptive Time Stepping for Dynamic Traffic Load Prediction in 6G Satellite Networks
by Yangan Zhang, Xiaoyu Zhang, Peng Yu and Xueguang Yuan
Electronics 2023, 12(21), 4473; https://doi.org/10.3390/electronics12214473 - 31 Oct 2023
Viewed by 836
Abstract
The rapid development of sixth-generation (6G) mobile broadband networks and Internet of Things (IoT) applications has led to significant increases in data transmission and processing, resulting in severe traffic congestion. To better allocate network resources, predicting network traffic has become crucial. However, satellite [...] Read more.
The rapid development of sixth-generation (6G) mobile broadband networks and Internet of Things (IoT) applications has led to significant increases in data transmission and processing, resulting in severe traffic congestion. To better allocate network resources, predicting network traffic has become crucial. However, satellite networks face global imbalances in IoT traffic demand, with substantial variations in satellite density and load distribution within the same constellation. These disparities render traditional traffic prediction algorithms inadequate for dynamically changing satellite network topologies. This paper thoroughly examines the impact of adaptive time stepping on the prediction of dynamic traffic load. Particularly, we propose a high-speed traffic prediction method that employs machine learning and recurrent neural networks over the 6G Space Air Ground Integration Network (SAGIN) structure. In our proposed method, we first investigate a variable step size-normalized least mean square (VSS-NLMS) adaptive prediction method for transforming time series prediction datasets. Then, we propose an adaptive time stepping-Gated Recurrent Unit (ATS-GRU) algorithm for real-time network traffic prediction. Finally, we compare the prediction accuracy of the ATS-GRU algorithm with that of the fixed time stepping-Gated Recurrent Unit (FTS-GRU) algorithm and compared the prediction results of three different step sizes (FSS, VSS, and ATS) based on normalized least mean square (NLMS). Numerical results demonstrate that our proposed scheme can automatically choose a suitable time stepping to track and predict the traffic load curve with acceptable accuracy and reasonable computational complexity, as its time stepping dynamically adjusts with the traffic. Full article
(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)
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14 pages, 840 KiB  
Article
Reconfigurable Intelligent Surface-Assisted Millimeter Wave Networks: Cell Association and Coverage Analysis
by Donglai Zhao, Gang Wang, Jinlong Wang and Zhiquan Zhou
Electronics 2023, 12(20), 4270; https://doi.org/10.3390/electronics12204270 - 16 Oct 2023
Cited by 2 | Viewed by 941
Abstract
Reconfigurable intelligent surface (RIS) is emerging as a promising technology to achieve coverage enhancement. This paper develops a tractable analytical framework based on stochastic geometry for performance analysis of RIS-assisted millimeter wave networks. Based on the framework, a two-step cell association criterion is [...] Read more.
Reconfigurable intelligent surface (RIS) is emerging as a promising technology to achieve coverage enhancement. This paper develops a tractable analytical framework based on stochastic geometry for performance analysis of RIS-assisted millimeter wave networks. Based on the framework, a two-step cell association criterion is proposed, and the analytical expressions of the user association probability and the coverage probability in general scenarios are derived. In addition, the closed-form expressions of the two performance metrics in special cases are also provided. The simulation results verify the accuracy of the theoretically derived analytical expressions, and reveal the superiority of deploying RISs in millimeter wave networks and the effectiveness of the proposed cell association scheme to improve coverage. Furthermore, the effects of the RIS parameters and the BS density on coverage performance are also investigated. Full article
(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)
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19 pages, 4533 KiB  
Article
6G IoT Tracking- and Machine Learning-Enhanced Blockchained Supply Chain Management
by Wei Liang, Lei Zhang and Michel Kadoch
Electronics 2023, 12(1), 40; https://doi.org/10.3390/electronics12010040 - 22 Dec 2022
Cited by 2 | Viewed by 1810
Abstract
The 6G Internet of Things (IoT) is of utmost importance when it comes to running and controlling contemporary supply chains. Blockchain and machine learning (ML) are two upper-layer technologies that can assist with securing and automating the IoT. First, we propose integrating blockchain [...] Read more.
The 6G Internet of Things (IoT) is of utmost importance when it comes to running and controlling contemporary supply chains. Blockchain and machine learning (ML) are two upper-layer technologies that can assist with securing and automating the IoT. First, we propose integrating blockchain technology into modern supply chains to facilitate effective communication among all partners. Second, for inbound logistics task prediction, we develop Multi-Head Attention (MHA)-Based Gated Recurrent Unit (GRU). Finally, numerical findings demonstrate that the MHA-Based GRU model has satisfying fitting efficiency and prediction precision compared to its competitors. Full article
(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)
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10 pages, 1802 KiB  
Article
Downlink MIMO-NOMA System for 6G Internet of Things
by Weiliang Xie, Xue Ding, Bowen Cai, Xiao Li and Mingshuo Wei
Electronics 2022, 11(19), 3233; https://doi.org/10.3390/electronics11193233 - 8 Oct 2022
Cited by 3 | Viewed by 1679
Abstract
This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA [...] Read more.
This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA system based on downlink simultaneous wireless information and power transfer (SWIPT) assistance. To improve the overall performance, we employ machine learning to optimize user-pairing and radio resource allocation. At the end of the paper, the simulation results are obtained, which fully prove that the MIMO-NOMA system constructed in this paper is correct in theory and can be realized in practice. Full article
(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)
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13 pages, 591 KiB  
Article
Channel Modeling for RIS-Assisted 6G Communications
by Xiuhua Fu, Rongqun Peng, Gang Liu, Jiazheng Wang, Wenhao Yuan and Michel Kadoch
Electronics 2022, 11(19), 2977; https://doi.org/10.3390/electronics11192977 - 20 Sep 2022
Cited by 4 | Viewed by 2592
Abstract
Terahertz communication has been proposed as one of the basic key technologies of the sixth-generation wireless network (6G) due to its significant advantages, such as ultra-large bandwidth, ultra-high transmission rates, high-precision positioning, and high-resolution perception. In terahertz-enabled 6G communication systems, the intelligent reconfiguration [...] Read more.
Terahertz communication has been proposed as one of the basic key technologies of the sixth-generation wireless network (6G) due to its significant advantages, such as ultra-large bandwidth, ultra-high transmission rates, high-precision positioning, and high-resolution perception. In terahertz-enabled 6G communication systems, the intelligent reconfiguration of wireless propagation environments by deploying reconfigurable intelligent surfaces (RIS) will be an important research direction. This paper analyzes the far field and near field of RIS-assisted wireless communication and a detailed system description is presented. Subsequently, this paper presents a specific study of the channel model for an RIS-assisted 6G communication system in the far-field and near-field cases, respectively. Finally, an integrated simulation of the channel models for the far-field and near-field cases is carried out, and the performance of the RIS auxiliary link measured in terms of signal-to-noise ratio (SNR) is compared and analyzed. The results show that increasing the size of the RIS surface to improve the SNR is an effective method to enhance the coverage performance of the 6G THz communication system under the strong guarantee of the ultra-large bandwidth of THz. Full article
(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)
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17 pages, 3289 KiB  
Article
A Framework and Method for Surface Floating Object Detection Based on 6G Networks
by He Li, Shuaipeng Yang, Jinjiang Liu, Yang Yang, Michel Kadoch and Tianyang Liu
Electronics 2022, 11(18), 2939; https://doi.org/10.3390/electronics11182939 - 16 Sep 2022
Cited by 2 | Viewed by 1367
Abstract
Water environment monitoring has always been an important method of water resource environmental protection. In practical applications, there are problems such as large water bodies, long monitoring periods, and large transmission and processing delays. Aiming at these problems, this paper proposes a framework [...] Read more.
Water environment monitoring has always been an important method of water resource environmental protection. In practical applications, there are problems such as large water bodies, long monitoring periods, and large transmission and processing delays. Aiming at these problems, this paper proposes a framework and method for detecting floating objects on water based on the sixth-generation mobile network (6G). Using satellite remote sensing monitoring combined with ground-truth data, a regression model is established to invert various water parameters. Then, using chlorophyll as the main reference indicator, anomalies are detected, early warnings are given in a timely manner, and unmanned aerial vehicles (UAVs) are notified through 6G to detect targets in abnormal waters. The target detection method in this paper uses MobileNetV3 to replace the VGG16 network in the single-shot multi-box detector (SSD) to reduce the computational cost of the model and adapt to the computing resources of the UAV. The convolutional block attention module (CBAM) is adopted to enhance feature fusion. A small target data enhancement module is used to enhance the network identification capability in the training process, and the key-frame extraction module is applied to simplify the detection process. The network model is deployed in system-on-a-chip (SOC) using edge computing, the processing flow is optimized, and the image preprocessing module is added. Tested in an edge environment, the improved model has a 2.9% increase in detection accuracy and is 55% higher in detection speed compared with SSD. The experimental results show that this method can meet the real-time requirements of video surveillance target detection. Full article
(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)
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