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Entropy
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Space-Air-Ground-Sea Integrated Communication Networks
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Space-Air-Ground-Sea Integrated Communication Networks

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 873

Special Issue Editors

Prof. Dr. Yanli Xu

E-Mail
Guest Editor
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: maritime communications; space–air–ground–sea integrated communication; edge computing; resource management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Shengming Jiang

E-Mail Website
Guest Editor
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: marine internet; best-effort networking systems; wireless networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the expansion of human activity and the rise of intelligent applications, communication network services need lower latency, higher capacity, and seamless coverage anywhere and anytime. Space–air–ground–sea integrated network (SAGSIN) integrates space-based networks, air-based networks, and ground-based as well as sea-based networks to form a much more complex system which can significantly enhance communication coverage and improve network service ability.

SAGSIN has attracted great attention on its architecture, resource management, communication network protocols, simulation studies, device demo design, etc. To promote the research of SAGSIN and the development of related industries, we organized the topic of “Space–Air–Ground–Sea Integrated Communication Networks” in Entropy to collect and publish recent innovative research and engineering application results. We welcome relevant experts, scholars, and researchers to submit their contributions. You are invited to submit papers and review articles that are related, but not limited, to the following topics of interests:

  1. Network architecture and protocols of SAGSIN;
  2. Performance analysis based on information theory for SAGSIN;
  3. Self-organization schemes of for SAGSIN;
  4. Resource allocation and management of SAGSIN;
  5. Cognitive radio of SAGSIN;
  6. Cloud computation and edge computation of SAGSIN;
  7. Interconnection and cooperation between heterogeneous networks in SAGSIN;
  8. QoS-aware algorithms, interference mitigation algorithms and energy-efficiency algorithms for SAGSIN;
  9. Cross-domain topology discovery of heterogeneous networks;
  10. Machine learning technologies for SAGSIN;
  11. New information theory for SAGSIN such as semantic communication;
  12. Network optimization based on game theory and other optimization tools;
  13. Simulation and experiment studies of SAGSIN.

Prof. Dr. Yanli Xu
Prof. Dr. Shengming Jiang
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. Entropy is an international peer-reviewed open access monthly 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

  • space–air–ground–sea integrated networks
  • resource management
  • topology discovery
  • network access protocols
  • communication protocols
  • network deployment
  • UAV ad hoc networks
  • satellite communications
  • maritime communications

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Published Papers (2 papers)

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Research

22 pages, 3428 KiB  
Article
Robust Smoothing Cardinalized Probability Hypothesis Density Filter-Based Underwater Multi-Target Direction-of-Arrival Tracking with Uncertain Measurement Noise
by Xinyu Gu, Xianghao Hou, Boxuan Zhang, Yixin Yang and Shuanping Du
Entropy 2025, 27(4), 438; https://doi.org/10.3390/e27040438 - 18 Apr 2025
Viewed by 43
Abstract
In view of the typical multi-target scenarios of underwater direction-of-arrival (DOA) tracking complicated by uncertain measurement noise in unknown underwater environments, a robust underwater multi-target DOA tracking method is proposed by incorporating Saga–Husa (SH) noise estimation and a backward smoothing technique within the [...] Read more.
In view of the typical multi-target scenarios of underwater direction-of-arrival (DOA) tracking complicated by uncertain measurement noise in unknown underwater environments, a robust underwater multi-target DOA tracking method is proposed by incorporating Saga–Husa (SH) noise estimation and a backward smoothing technique within the framework of the cardinalized probability hypothesis density (CPHD) filter. First, the kinematic model of underwater targets and the measurement model based on the received signals of a hydrophone array are established, from which the CPHD-based multi-target DOA tracking algorithm is derived. To mitigate the adverse impact of uncertain measurement noise, the Saga–Husa approach is deployed for dynamic noise estimation, thereby reducing noise-induced performance degradation. Subsequently, a backward smoothing technique is applied to the forward filtering results to further enhance tracking robustness and precision. Finally, extensive simulations and experimental evaluations demonstrate that the proposed method outperforms existing DOA estimation and tracking techniques in terms of robustness and accuracy under uncertain measurement noise conditions. Full article
(This article belongs to the Special Issue Space-Air-Ground-Sea Integrated Communication Networks)
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23 pages, 1454 KiB  
Article
Slot Allocation Protocol for UAV Swarm Ad Hoc Networks: A Distributed Coalition Formation Game Approach
by Liubin Song and Daoxing Guo
Entropy 2025, 27(3), 256; https://doi.org/10.3390/e27030256 - 28 Feb 2025
Viewed by 603
Abstract
With the rapid development of unmanned aerial vehicle (UAV) manufacturing technology, large-scale UAV swarm ad hoc networks are becoming widely used in military and civilian spheres. UAV swarms equipped with ad hoc networks and satellite networks are being developed for 6G heterogeneous networks, [...] Read more.
With the rapid development of unmanned aerial vehicle (UAV) manufacturing technology, large-scale UAV swarm ad hoc networks are becoming widely used in military and civilian spheres. UAV swarms equipped with ad hoc networks and satellite networks are being developed for 6G heterogeneous networks, especially in offshore and remote areas. A key operational aspect in large-scale UAV swarm networks is slot allocation for large capacity and a low probability of conflict. Traditional methods typically form coalitions among UAVs that are in close spatial proximity to reduce internal network interference, thereby achieving greater throughput. However, significant internal interference still persists. Given that UAV networks are required to transmit a substantial amount of safety-related control information, any packet loss due to internal interference can easily pose potential risks. In this paper, we propose a distributed time coalition formation game algorithm that ensures the absence of internal interference and collisions while sharing time slot resources, thereby enhancing the network’s throughput performance. Instead of forming a coalition from UAVs within a contiguous block area as used in prior studies, UAV nodes with no interference from each other form a coalition that can be called a time coalition. UAVs belonging to one coalition share their transmitting slots with each other, and thus, every UAV node achieves the whole transmitting slots of coalition members. They can transmit data packets simultaneously with no interference. In addition, a distributed coalition formation game-based TDMA (DCFG-TDMA) protocol based on the distributed time coalition formation algorithm is designed for UAV swarm ad hoc networks. Our simulation results verify that the proposed algorithm can significantly improve the UAV throughput compared with that of the conventional TDMA protocol. Full article
(This article belongs to the Special Issue Space-Air-Ground-Sea Integrated Communication Networks)
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