Hybrid Satellite-UAV-Terrestrial Networks for 6G Ubiquitous Coverage

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

Deadline for manuscript submissions: 15 October 2024 | Viewed by 3550

Special Issue Editors

Department Of Electronic Engineering, Tsinghua University, Beijing 100084, China
Interests: maritime communication networks; large-scale distributed antenna systems; coordinated satellite-UAV-terrestrial networks
Special Issues, Collections and Topics in MDPI journals
School of Engineering, University of Warwick, Coventry CV4 7AL, UK
Interests: wireless communications; performance analysis; joint radar-communications designs; cognitive radios; wireless relaying; energy harvesting
Special Issues, Collections and Topics in MDPI journals
School of Information Science and Technology, Nantong University, Nantong 226019, China
Interests: MIMO/massive MIMO wireless communications; machine learning in communication system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The future sixth-generation (6G) network is intended to cover remote areas to tackle the digital divide. Both satellites and unmanned aerial vehicles (UAVs) play vital roles in achieving this goal. Considering the vastness of remote areas and the sparsity of users therein, the integration of satellites, UAVs, and still-available terrestrial infrastructures into a hybrid satellite-UAV-terrestrial network (HSUTN) is promising for more agile and more efficient coverage.

This Special Issue seeks to bring together state-of-the-art original research and the latest advancements and innovations in theories, key technologies, and innovative applications of 6G HSUTNs. 

We seek high-quality, original research papers regarding topics including, but not limited to: 

  • AI-native and secure HSUTN architecture;
  • Integrated sensing and communication for HSUTNs;
  • MIMO/RIS for enhancing HSUTNs;
  • Physical layer security issues in HSUTNs;
  • Mobile edge computing for HSUTNs;
  • Advanced non-orthogonal multiple access technologies for HSUTNs;
  • Resource orchestration for HSUTNs;
  • Delay-control techniques in HSUTNs;
  • Artificial intelligence approaches for agile HSUTNs;
  • Hardware testbed or field trial for HSUTNs.

Prof. Dr. Wei Feng 
Dr. Yunfei Chen
Dr. Jue Wang
Guest Editors

Manuscript Submission Information

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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

  • sixth-generation (6G) network
  • hybrid satellite-UAV-terrestrial network
  • agile coverage

Published Papers (3 papers)

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Research

17 pages, 834 KiB  
Article
A FL-Based Radio Map Reconstruction Approach for UAV-Aided Wireless Networks
by Zhiqiang Tan, Limin Xiao, Xinyi Tang, Ming Zhao and Yunzhou Li
Electronics 2023, 12(13), 2817; https://doi.org/10.3390/electronics12132817 - 26 Jun 2023
Cited by 1 | Viewed by 1044
Abstract
Radio maps, which can provide metrics for signal strength at any location in a geographic space, are useful for many applications of 6G technologies, including UAV-assisted communication, network planning, and resource allocation. However, current crowd-sourced reconstruction methods necessitate large amounts of privacy-sensitive user [...] Read more.
Radio maps, which can provide metrics for signal strength at any location in a geographic space, are useful for many applications of 6G technologies, including UAV-assisted communication, network planning, and resource allocation. However, current crowd-sourced reconstruction methods necessitate large amounts of privacy-sensitive user data and entail the training of all data with large models, especially in deep learning. This poses a threat to user privacy, reducing the willingness to provide data, and consuming significant server resources, rendering the reconstruction of radio maps on resource-constrained UAVs challenging. To address these limitations, a self-supervised federated learning model called RadioSRCNet is proposed. The model utilizes a super-resolution (SR)-based network and feedback training strategy to predict the pathloss for continuous positioning. In our proposition, users retain the original data locally for training, acting as clients, while the UAV functions as a server to aggregate non-sensitive data for radio map reconstruction in a federated learning (FL) manner. We have employed a feedback training strategy to accelerate convergence and alleviate training difficulty. In addition, we have introduced an arbitrary position prediction (APP) module to decrease resource consumption in clients. This innovative module struck a balance between spatial resolution and computational complexity. Our experimental results highlight the superiority of our proposed framework, as our model achieves higher accuracy while incurring less communication overheads in a computationally and storage-efficient manner as compared to other deep learning methods. Full article
(This article belongs to the Special Issue Hybrid Satellite-UAV-Terrestrial Networks for 6G Ubiquitous Coverage)
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20 pages, 1198 KiB  
Article
A Novel Dynamic Transmission Power of Cluster Heads Based Clustering Scheme
by Mengchu Nie, Pingmu Huang, Jie Zeng, Yueming Lu, Tao Zhang and Tiejun Lv
Electronics 2023, 12(3), 619; https://doi.org/10.3390/electronics12030619 - 26 Jan 2023
Cited by 1 | Viewed by 996
Abstract
Clustering methods are promising tools for ensuring the network scalability and maintainability of large-scale flying ad hoc networks (FANETs). However, due to the high mobility and limited energy resources of unmanned aerial vehicles (UAVs), it is difficult to maintain the network reliability and [...] Read more.
Clustering methods are promising tools for ensuring the network scalability and maintainability of large-scale flying ad hoc networks (FANETs). However, due to the high mobility and limited energy resources of unmanned aerial vehicles (UAVs), it is difficult to maintain the network reliability and extend the network life of FANETs. In this paper, a new K-means algorithm is developed, and a dynamic transmission power of the cluster heads based clustering (DTPCH-C) scheme is proposed. The goal of this scheme is presented for FANETs to improve the reliability and lifetime of FANETs. Firstly, the optimal number of clusters is calculated and the initial UAV clusters are set up by a K-means algorithm. Then, using a weighted clustering algorithm, the adaptive node degree, the node energy and the distance from the cluster head are weighted and summed for the cluster head election. In the process of inter-cluster communication, the cluster head adjusts its transmit power in real-time through meshing and mobile prediction, thus saving the energy consumption and improving the network lifetime. The proposed DTPCH-C simultaneously optimizes the cluster number, the cluster head energy consumption, the selected cluster head, and the cluster maintenance process. The simulation results show that compared with traditional clustering methods, the proposed DTPCH-C has obvious advantages in terms of the network reliability, network life, and energy consumption. Full article
(This article belongs to the Special Issue Hybrid Satellite-UAV-Terrestrial Networks for 6G Ubiquitous Coverage)
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13 pages, 1245 KiB  
Article
IRS-Based UAV-Assisted Low-Altitude Passive Relaying: SER Performance Analysis of Optimal Deployment
by Tianhe Li, Minghe Mao, Mengjie Xu, Yang He, Ye Feng and Rui Shi
Electronics 2022, 11(20), 3306; https://doi.org/10.3390/electronics11203306 - 14 Oct 2022
Viewed by 923
Abstract
This paper presents a method for analyzing the symbol error rate (SER) of a UAV cellular data network based on an IRS. This method can change the distances between the BS, IRS, UAV, and the elevation of the UAV to observe their impacts [...] Read more.
This paper presents a method for analyzing the symbol error rate (SER) of a UAV cellular data network based on an IRS. This method can change the distances between the BS, IRS, UAV, and the elevation of the UAV to observe their impacts on the SER; then, a two-dimensional curve diagram of the parameters and the SER is drawn to determine the deployment position of the UAV. Finally, by flexibly changing the maximum angle of the UAV’s transmitted signal and the height of the UAV, the coverage area of the UAV’s cellular data network can be obtained through three-dimensional imaging, function fitting, and the extreme value of the condition function. As a relay of a cellular data network, a UAV can be flexibly deployed at any effective position at a low altitude to compensate for the limited coverage of the base station and the poor quality of the user’s received signal. In particular, an IRS deployed on the surface of a building can generate an equivalent line-of-sight channel to reflect the signal from the base station to the UAV. Using an IRS to change the signal phase and amplitude with the flexible deployment of UAVs can give priority to solving the problems of cellular data network coverage and signal quality in urban scenarios. Full article
(This article belongs to the Special Issue Hybrid Satellite-UAV-Terrestrial Networks for 6G Ubiquitous Coverage)
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