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Special Issue "The Convergence of Remote Sensing, Communication, and Computing for 6G Space-Air-Ground Integrated Networks"

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: 15 December 2023 | Viewed by 5714

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Special Issue Editors

Prof. Dr. Chen Chen

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State Key Laboratory of Integrated Services Networks, Xidian University, No.2 Taibai Road, Xi'an 70071, China
Interests: internet of things; intelligent transportation systems; wireless communications
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Dr. Ying Ju

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State Key Laboratory of Integrated Services Networks, Xidian University, No. 2 Taibai Road, Xi’an 70071, China
Interests: wireless communication security; mmWave commiunications; satellite networks

Prof. Dr. Shaohua Wan
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Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China
Interests: deep learning; internet of things; edge computing
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Dr. Stefano Berretti

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Media Integration and Communication Center (MICC), Department of Information Engineering (DINFO), University of Firenze, Via S. Marta 3, 50139 Firenze, Italy
Interests: multimedia; 3D computer vision; articifial intelligence
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Prof. Dr. Michele Nappi

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Department of Computer Science, University of Salerno Fisciano, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy
Interests: multibiometric systems; pattern recognition; image processing; compression and indexing; multimedia databases; human-computer interaction; VR/AR

Special Issue Information

Dear Colleagues,

As the trajectory of human mobility continues to expand, the need for communication in deserts, oceans, and other places is also increasing. In this context, global communication coverage can be achieved through 6G space–air–ground integration technology. For the high Earth orbit (HEO) satellites, the transmission delay over long distances has greatly affected the development of satellite communication technology. At the same time, in terms of wide-area Internet of Things (IoT) perception, such as environmental monitoring, smart agriculture, and intelligent power grid, the low Earth orbit (LEO) satellite platform only serves as a collection and return facility for IoT nodes. Massive data still need to be sent back to the ground stations for processing. Meanwhile, detecting and tracking high-mobility targets are not timely enough, and further improvement is needed in terms of low service delay and timely remote sensing information feedback. This requires the guarantee of satellite computing capability. The integration of edge computing technology into the satellite communication network and remote sensing will greatly reduce the service time, improve the quality of satellite communication service, and strengthen the satellite task processing capability so as to enhance the performance of the space–air–ground integrated network (SAGIN) to a greater extent.

Prof. Dr. Chen Chen
Dr. Ying Ju
Prof. Dr. Shaohua Wan
Dr. Stefano Berretti
Prof. Dr. Michele Nappi
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. Remote Sensing 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 2700 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

integration of remote sensing, communication, and computing for 6G SAGIN
distributed intelligence-aided sensing, communication, and computing for 6G SAGIN
blockchain-empowered 6G SAGIN
security and privacy issues for the integration of sensing, communication, and computing in 6G SAGIN
sensing and communication coexistence/spectrum sharing in 6G SAGIN
system-level simulation, prototyping, and field tests for 6G SAGIN

Published Papers (4 papers)

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Research

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Open AccessArticle

Infrared and Visible Image Homography Estimation Based on Feature Correlation Transformers for Enhanced 6G Space–Air–Ground Integrated Network Perception

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Remote Sens. 2023, 15(14), 3535; https://doi.org/10.3390/rs15143535 - 13 Jul 2023

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Abstract

The homography estimation of infrared and visible images, a key technique for assisting perception, is an integral element within the 6G Space–Air–Ground Integrated Network (6G SAGIN) framework. It is widely applied in the registration of these two image types, leading to enhanced environmental perception and improved efficiency in perception computation. However, the traditional estimation methods are frequently challenged by insufficient feature points and the low similarity in features when dealing with these images, which results in poor performance. Deep-learning-based methods have attempted to address these issues by leveraging strong deep feature extraction capabilities but often overlook the importance of precisely guided feature matching in regression networks. Consequently, exactly acquiring feature correlations between multi-modal images remains a complex task. In this study, we propose a feature correlation transformer method, devised to offer explicit guidance for feature matching for the task of homography estimation between infrared and visible images. First, we propose a feature patch, which is used as a basic unit for correlation computation, thus effectively coping with modal differences in infrared and visible images. Additionally, we propose a novel cross-image attention mechanism to identify correlations between varied modal images, thus transforming the multi-source images homography estimation problem into a single-source images problem by achieving source-to-target image mapping in the feature dimension. Lastly, we propose a feature correlation loss (FCL) to induce the network into learning a distinctive target feature map, further enhancing source-to-target image mapping. To validate the effectiveness of the newly proposed components, we conducted extensive experiments to demonstrate the superiority of our method compared with existing methods in both quantitative and qualitative aspects. Full article

(This article belongs to the Special Issue The Convergence of Remote Sensing, Communication, and Computing for 6G Space-Air-Ground Integrated Networks)

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Open AccessArticle

Distributed Coordination of Space–Ground Multiresources for Remote Sensing Missions

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Remote Sens. 2023, 15(13), 3362; https://doi.org/10.3390/rs15133362 - 30 Jun 2023

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Abstract

As data relay satellites (DRSs) play an increasingly important supporting role in remote sensing missions, efficient coordination across space–ground multiresources becomes a significant problem. Owing to the implementation problem of the centralized coordinate methods, this paper studies a distributed coordinate resource scheduling method which is realizable in the current space network structure. To be specific, we first formulate the multiple resource coordination problem into an MILP problem based on a modified time-expanded graph. Then, the problem is transferred and decomposed into subproblems for remote sensing satellite (RSS) systems and DRS systems to solve distributedly. Afterwards, we propose a distributed iterative scheme for the RSS systems and DRS systems based on alternating direction method of multipliers (ADMM), in which only the schedule information of the inter-satellite links are required to exchange between RSS systems and DRS systems. Simulation results are provided to validate the effectiveness of our distributed coordinated resource scheduling algorithm. Full article

(This article belongs to the Special Issue The Convergence of Remote Sensing, Communication, and Computing for 6G Space-Air-Ground Integrated Networks)

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Open AccessArticle

DRL-Based Load-Balancing Routing Scheme for 6G Space–Air–Ground Integrated Networks

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Remote Sens. 2023, 15(11), 2801; https://doi.org/10.3390/rs15112801 - 28 May 2023

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Abstract

Due to the rapid development of the space–air–ground integrated network (SAGIN), a satellite communication system has the advantages of wide coverage and low requirements for a geographical environment and is gradually becoming the main competitive technology for 6G. The low-earth-orbit (LEO) satellite network has the characteristics of low transmission delay, small propagation loss, and global coverage, and its exploration has become the main research object of contemporary satellite communications. However, traditional routing algorithms cannot adapt to the characteristics of the high dynamics and load-balancing requirements of LEO satellite networks. In this paper, a load-balancing routing algorithm for LEO satellites based on Deep Q-Network (DQN-LLRA) is proposed by using deep reinforcement learning. Making use of the model obtained by the DQN training, satellite nodes can select the best routing results according to the delay, bandwidth, and queue utilization of the surrounding satellite nodes. The simulation and analysis show that the path load obtained by the proposed algorithm is low. Compared with the Q-learning-based algorithm, this algorithm reduces the maximum queue utilization rate of the routing path by 5%, reduces the average queue utilization rate of the routing path by 13%, and effectively balances the load in the network. Full article

(This article belongs to the Special Issue The Convergence of Remote Sensing, Communication, and Computing for 6G Space-Air-Ground Integrated Networks)

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Review

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Open AccessReview

An Overview of Emergency Communication Networks

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Remote Sens. 2023, 15(6), 1595; https://doi.org/10.3390/rs15061595 - 15 Mar 2023

Cited by 2 | Viewed by 3150

Abstract

In recent years, major natural disasters and public safety accidents have frequently occurred worldwide. In order to deal with various disasters and accidents using rapidly deployable, reliable, efficient, and stable emergency communication networks, all countries in the world are strengthening and improving emergency communication network construction and related technology research. Motivated by these situations, in this paper, we provide a state-of-the-art survey of the current situation and development of emergency communication networks. In this detailed investigation, our primary focus is the extensive discussion of emergency communication network technology, including satellite networks, ad hoc networks, cellular networks, and wireless private networks. Then, we explore and analyze the networks currently applied in emergency rescue, such as the 370M narrowband private network, broadband cluster network, and 5G constellation plan. We propose a broadband-narrowband integrated emergency communication network to provide an effective solution for visual dispatch of emergency rescue services. The main findings derived from the comprehensive survey on the emergency communication network are then summarized, and possible research challenges are noted. Lastly, we complete this survey by shedding new light on future directions for the emergency communication network. In the future, the emergency network will develop in the direction of intelligence, integration, popularization, and lower cost, and space-air-ground-sea integrated networks. This survey provides a reference basis for the construction of networks to mitigate major natural disasters and public safety accidents. Full article

(This article belongs to the Special Issue The Convergence of Remote Sensing, Communication, and Computing for 6G Space-Air-Ground Integrated Networks)

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