Integrated Communication, Navigation, and Remote Sensing in Leo Networks with Vehicular Applications
Min Sheng, Chongtao Guo, Lei Huang
Abstract
Traditionally, communication, navigation, and remote sensing (CNR) satellites perform separately, leading to resource waste, information isolation, and independent optimization for each functionality. As an example, future automated driving 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 resources, and data information, toward 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.