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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.10969 |
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| _version_ | 1866909320193507328 |
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| author | Sheng, Min Guo, Chongtao Huang, Lei |
| author_facet | Sheng, Min Guo, Chongtao Huang, Lei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10969 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Integrated Communication, Navigation, and Remote Sensing in LEO Networks with Vehicular Applications Sheng, Min Guo, Chongtao Huang, Lei Information Theory 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. |
| title | Integrated Communication, Navigation, and Remote Sensing in LEO Networks with Vehicular Applications |
| topic | Information Theory |
| url | https://arxiv.org/abs/2404.10969 |