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Integrated Communication, Navigation, and Remote Sensing in LEO Networks with Vehicular Applications

Min Sheng, Chongtao Guo, Lei Huang

TL;DR

An integrated CNR (ICNR) framework based on low Earth orbit (LEO) satellite mega-constellations is proposed, which sheds strong light on qualitative performance improvement by sophisticatedly sharing orbit constellation, wireless resources, and data information, toward meeting the requirements of vehicular applications.

Abstract

Traditionally, communication, navigation, and remote sensing (CNR) satellites are separately performed, leading to resource waste, information isolation, and independent optimization for each functionality. Taking future automated driving as an example, it faces great challenges in providing high-reliable and low-latency lane-level positioning, decimeter-level transportation observation, and huge traffic sensing information downloading. To this end, this article proposes an integrated CNR (ICNR) framework based on low Earth orbit (LEO) satellite mega-constellations. After introducing the main working principles of the CNR functionalities to serve as the technological basis, we characterize the potentials of the integration gain in vehicular use cases. Then, we investigate the ICNR framework in different integration levels, which sheds strong light on qualitative performance improvement by sophisticatedly sharing orbit constellation, wireless resource, and data information towards meeting the requirements of vehicular applications. We also instantiate a fundamental numerical case study to demonstrate the integration gain and highlight possible future research directions in managing the ICNR networks.

Integrated Communication, Navigation, and Remote Sensing in LEO Networks with Vehicular Applications

TL;DR

An integrated CNR (ICNR) framework based on low Earth orbit (LEO) satellite mega-constellations is proposed, which sheds strong light on qualitative performance improvement by sophisticatedly sharing orbit constellation, wireless resources, and data information, toward meeting the requirements of vehicular applications.

Abstract

Traditionally, communication, navigation, and remote sensing (CNR) satellites are separately performed, leading to resource waste, information isolation, and independent optimization for each functionality. Taking future automated driving as an example, it faces great challenges in providing high-reliable and low-latency lane-level positioning, decimeter-level transportation observation, and huge traffic sensing information downloading. To this end, this article proposes an integrated CNR (ICNR) framework based on low Earth orbit (LEO) satellite mega-constellations. After introducing the main working principles of the CNR functionalities to serve as the technological basis, we characterize the potentials of the integration gain in vehicular use cases. Then, we investigate the ICNR framework in different integration levels, which sheds strong light on qualitative performance improvement by sophisticatedly sharing orbit constellation, wireless resource, and data information towards meeting the requirements of vehicular applications. We also instantiate a fundamental numerical case study to demonstrate the integration gain and highlight possible future research directions in managing the ICNR networks.
Paper Structure (13 sections, 5 figures, 1 table)

This paper contains 13 sections, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. ICNR Framework with Vehicular Applications
  3. Satellite Communication
  4. Satellite Navigation
  5. Satellite Remote Sensing
  6. Proposed ICNR Framework
  7. Integration Levels of ICNR
  8. A Fundamental Case Study
  9. Future Research Directions
  10. Constellation Design
  11. Satellite Association
  12. Resource Management
  13. Conclusion

Figures (5)

  • Figure 1: Fundamental working principles of satellite communication, navigation, and remote sensing.
  • Figure 2: Illustration of the proposed ICNR framework with vehicular applications considered in representative rural and urban use cases.
  • Figure 3: Key components and working mechanisms of four different integration levels of the proposed ICNR framework.
  • Figure 4: Estimated gain of function-level and signal-level integration.
  • Figure 5: Preferable satellite association relationship for CNR functionalities.