The integration of Semantic Communications (SemCom) and edge computing in space networks enables the optimal allocation of the scarce energy, computing, and communication resources for data-intensive applications. We use Earth Observation (EO) as a canonical functionality of satellites and review its main characteristics and challenges. We identify the potential of the space segment, represented by a low Earth orbit (LEO) satellite constellation, to serve as an edge layer for distributed intelligence. Based on that, propose a system architecture that supports semantic and goal-oriented applications for image reconstruction and object detection and localization. The simulation results show the intricate trade-offs among energy, time, and task-performance using a real dataset and State-of-the-Art (SoA) processing and communication parameters.
@article{arxiv.2408.15639,
title = {Semantic and goal-oriented edge computing for satellite Earth Observation},
author = {Beatriz Soret and Israel Leyva-Mayorga and Antonio M. Mercado-Martínez and Marco Moretti and Antonio Jurado-Navas and Marc Martinez-Gost and Celia Sánchez de Miguel and Ainoa Salas-Prendes and Petar Popovski},
journal= {arXiv preprint arXiv:2408.15639},
year = {2024}
}
Comments
Submitted for publication to IEEE Communications Magazine