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Intelligent Sensing, Computing, Caching, and Networking Technologies for Space-Air-Ground Integrated Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 25 August 2025 | Viewed by 651

Special Issue Editors

School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China
Interests: network security; software-defined networks; satellite networks; mobile internet
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Interests: network security; Internet of Things; service function chains; mobile internet

E-Mail Website
Guest Editor
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Interests: unmanned aerial vehicles; ad hoc networks; communication performance

Special Issue Information

Dear Colleagues,

Space–Air–Ground Integrated Networks (SAGINs) have recently gained great attention from both academia and industry and are seen as an important evolutional direction for the next-generation information networks, aiming to achieve user access and service provision anytime and anywhere. However, SAGINs are still facing many technical obstacles due to the heterogeneity of the space, air and ground networks. Fortunately, with many new advanced techniques such as Software-Defined Networks (SDNs), Network Function Virtualization (NFV), Service Function Chains (SFCs) and Machine Learning (ML), network control and management can be greatly facilitated for network integration, resource allocation, traffic steering, content caching, service orchestration and security enhancement, which provide an alternative way to cope with many key challenges not addressed in SAGINs.

This Special Issue focuses on any intelligent sensing, computing, caching and networking technologies for SAGINs, and the purpose is to promote corresponding researchers and experts to present their novel ideas and recent findings, shedding light on the rapid development of this field. Original research and review papers are both welcomed.
Potential topics include, but are not limited to, the following:
  • Intelligent sensing and computing for SAGINs;
  • Heterogeneous network convergence for SAGINs;
  • Centralized/distributed routing mechanism for SAGINs;
  • Security and privacy protection mechanism for SAGINs;
  • ML-based algorithms for resource allocation, traffic steering, content caching and service orchestration in SAGINs. 

Dr. Bohao Feng
Prof. Dr. Huachun Zhou
Dr. Yuming Zhang
Prof. Dr. Ilsun You
Guest Editors

Manuscript Submission Information

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Keywords

  • sensing
  • computing
  • caching
  • networking
  • space–air–ground integrated networks

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Published Papers (1 paper)

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Research

17 pages, 1589 KiB  
Article
An Efficient Quantized Message Passing Receiver Design for SCMA Systems
by Hao Cheng, Min Zhang and Ruoyu Su
Sensors 2025, 25(10), 3098; https://doi.org/10.3390/s25103098 - 14 May 2025
Viewed by 180
Abstract
Sparse code multiple access (SCMA) has been considered as an efficient technique to provide both massive connectivity and high spectrum efficiency for future machine-type wireless networks. However, the conventional uniform quantization of the message passing algorithm (MPA) for the SCMA detection induces a [...] Read more.
Sparse code multiple access (SCMA) has been considered as an efficient technique to provide both massive connectivity and high spectrum efficiency for future machine-type wireless networks. However, the conventional uniform quantization of the message passing algorithm (MPA) for the SCMA detection induces a significant bit error ratio (BER) performance degradation. In this sense, we propose a new quasi-uniform quantization scheme that can efficiently handle the dynamic range in the exchange of messages. To accelerate the convergence of conventional Max-log MPA, the Sub-log MPA is considered by using the latest updating messages at the current iteration. Simulation results show that the proposed quasi-uniform quantization method can significantly improve the BER performance of the SCMA decoder without modifying the resource nodes’ and variable nodes’ update rules in both the additive white Gaussian noise and the Rayleigh frequency selective channels, as compared to the uniform quantizer. Full article
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