Skip to main content

AI Enabled Signal Processing for Space-Air-Ground Integrated Internet of Things

Guest Editors:

Xin Liu: Dalian University of Technology, China
Jing Jiang: University of Northumbria, UK
Zhengguo Sheng: University of Sussex, Brighton, UK
Qiuming Zhu: Nanjing University of Aeronautics and Astronautics, China
Soufiene Djahel: University of Huddersfield, UK

Submission Status: Closed | Submission Deadline: Closed

This collection is no longer accepting submissions.

With the rapid development of industrial production, Internet of Things (IoT) will experience significant expansion in both spatial scope and communication content. Various IoT services will cover diverse areas such as oceans, sky, deep space, and beyond. However, deploying large-scale base stations in wide-area ground 5G networks comes with high construction and maintenance costs. Additionally, the ground network faces challenges in providing coverage to remote areas. The Space-Air-Ground Integrated IoT is a concept that refers to the integration of satellite networks, aviation networks, and ground networks to create a comprehensive and interconnected IoT ecosystem. This integrated approach aims to overcome the limitations of traditional IoT deployments, particularly in remote and challenging environments. The Space-Air-Ground Integrated IoT envisions a network of interconnected devices, sensors, and systems that can communicate and share data seamlessly across different dimensions, including space, air, and ground. This integration allows for a wide range of applications and use cases, ranging from environmental monitoring, disaster management, transportation, agriculture, logistics, and beyond. However, due to the distinct structural characteristics of space, air, and ground networks, the signal processing for Space-Air-Ground Integrated IoT is more complex compared to ground networks. Artificial intelligence (AI) is considered a promising solution for addressing these complex network problems.

AI-enabled signal fusion can be employed to integrate signals from multiple sources, such as satellite-based sensors, airborne drones, and ground-based sensors, to obtain a more comprehensive and accurate understanding of the environment. AI-enabled anomaly detection can analyze the vast amount of data generated by Space-Air-Ground Integrated IoT systems to identify abnormal behavior, events, or patterns that may indicate potential security threats or system malfunctions. AI-enabled predictive maintenance can analyze sensor data from space, air, and ground-based devices to predict equipment failures, optimize maintenance schedules, and reduce downtime. AI-enabled energy management can optimize the energy consumption of IoT devices by dynamically adjusting their communication parameters, scheduling transmissions, and managing energy resources based on changing environmental conditions. AI-enabled spectrum management can dynamically allocate and optimize space-air-ground integrated spectrum resources based on real-time traffic patterns, interference conditions, and network requirements, enabling efficient spectrum utilization and avoiding interference.

  1. Interrupted-sampling repeater jamming (ISRJ) is a type of intra-pulse coherent jamming that poses a significant threat to radar detection and tracking of targets. This paper proposes an ISRJ suppression method...

    Authors: Yunhao Ji, Shan Wei and Yaobing Lu
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:55
  2. As a critical component of space-air-ground integrated IoT, the aerial network provides highly reliable, low-latency and ubiquitous information services to ground users by virtue of their high mobility, easy d...

    Authors: Yuhuai Peng, Xiaoliang Guang, Xinyu Zhang, Lei Liu, Cemulige Wu and Lei Huang
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:54
  3. Specific emitter identification is pivotal in both military and civilian sectors for discerning the unique hardware distinctions inherent to various launchers, it can be used to implement security in wireless ...

    Authors: Dingshan Li, Bin Yao, Pu Sun, Peitong Li, Jianfeng Yan and Juzhen Wang
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:42
  4. Cellular-connected unmanned aerial vehicles (UAVs), which have the potential to extend cellular services from the ground into the airspace, represent a promising technological advancement. However, the presenc...

    Authors: Weizhi Zhong, Xin Wang, Xiang Liu, Zhipeng Lin and Farman Ali
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:35
  5. Space-air-ground integrated networks comprise a multi-level heterogeneous integrated network that combines satellite-based, aerial, and terrestrial networks. With the increasing human exploration of space and ...

    Authors: Wuzhou Nie, Yong Chen, Yuhao Wang, Peizheng Wang, Meng Li and Lei Ning
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:34
  6. Unmanned aerial vehicles (UAVs) offer a new approach to wireless communication, leveraging their high mobility, flexibility, and visual communication capabilities. Ambient backscatter communication enables Int...

    Authors: Cheng Zhong, Di Zhai, Yang Lu and Ke Li
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:30
  7. As the scale of water conservancy projects continues to expand, the amount and complexity of analytical data have also correspondingly increased. At present, it is difficult to realize project management decis...

    Authors: Zhen Liu, Sen Chen, Zhaobo Zhang, Jiahao Qin and Bao Peng
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:29
  8. In recent years, UAV techniques are developing very fast, and UAVs are becoming more and more popular in both civilian and military fields. An important application of UAVs is rescue and disaster relief. In po...

    Authors: Liang Ye, Yu Yang, Weixiao Meng, Xuanli Wu, Xiaoshuai Li and Rangang Zhu
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:21
  9. Equipment failures and communication interruptions of satellites, aircraft and ground devices lead to data loss in Space-Air-Ground Integrated Internet of Things (SAGIoT). The incomplete data affect the accura...

    Authors: Lantu Guo, Yuchao Liu, Yuqian Li and Kai Yang
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:125
  10. The emerging Space-Air-Ground, Artificial intelligence, blockchain and Vehicle-to-everything technology in Integrated Internet of Things (IoT) enables vehicles to communicate with other vehicles and roadside u...

    Authors: Wei Liang, Jun Zhao, Yan Liu, Yan Liang and Jingwen Li
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:115
  11. As massive MIMO is a key technology in the future sixth generation (6G), the large-scale antenna arrays are widely considered in direction-of-arrival (DOA) estimation for they can provide larger aperture and h...

    Authors: Yifan Li, Baihua Shi, Feng Shu, Yaoliang Song and Jiangzhou Wang
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:110
  12. In complex industrial environments such as the Internet of Things in coal mines, large mechanical and electrical equipment can generate powerful impulsive noise, which can cause sudden errors. Because it is di...

    Authors: Bin Wang, Ziyan Jiang, Yanjing Sun and Yan Chen
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:104
  13. With the inherent advantages of exceptional maneuverability, flexible deployment options and cost-effectiveness, unmanned aerial vehicles (UAVs) present themselves as a viable solution for providing aerial com...

    Authors: Ruibo Han, Yongjian Wang and Yang Zhang
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:97

About the collection

This special section invites original research and practical contributions that advance AI-enabled signal processing for Space-Air-Ground Integrated IoT, covering topics related to architecture, technologies, and applications. Surveys and state-of-the-art tutorials are also welcomed.

This special section will focus on (but not limited to) the following topics:

• Machine learning methods for signal processing in Space-Air-Ground Integrated IoT
• Edge computing for signal processing in Space-Air-Ground Integrated IoT
• AI enabled signal processing for Space-Air-• Ground Integrated IoT
• AI-enabled predictive maintenance for Space-Air-Ground Integrated IoT
• AI-enabled anomaly detection for Space-Air-Ground Integrated IoT
• AI enabled spectrum management for Space-Air-Ground Integrated IoT
• AI enabled information security for Space-Air-Ground Integrated IoT
• AI enabled energy-efficiency and spectrum-efficiency optimization for Space-Air-Ground Integrated IoT
• New architectures and applications of AI enabled Space-Air-Ground Integrated IoT

Image credit: @Blue Planet Studio /