A Joint JSCC-Resource Allocation Framework for QoS-Aware Semantic Communication in LEO Satellite-based EO Missions
Hung Nguyen-Kha, Ti Ti Nguyen, Vu Nguyen Ha, Eva Lagunas, Symeon Chatzinotas, Bjorn Ottersten

TL;DR
This paper presents a joint optimization framework combining semantic communication and resource allocation for LEO satellite Earth observation missions, significantly reducing power consumption while maintaining image quality.
Contribution
It introduces a novel joint JSCC-resource allocation method with a curve-fitting model to optimize power efficiency under QoS constraints in satellite communications.
Findings
Achieves substantial power savings over traditional methods.
Effectively balances image quality and transmission power.
Demonstrates robustness in dynamic LEO satellite conditions.
Abstract
In Earth observation (EO) missions with Low Earth orbit (LEO) satellites, high-resolution image acquisition generates a massive data volume that poses a significant challenge for transmission under the limited satellite power budget, while LEO movement introduces dynamic systems. To enable efficient image transmission, this paper employs semantic communication (SemCom) with joint source-channel coding (JSCC), which focuses on transmitting meaningful information to reduce power consumption. Under a quality-of-service (QoS) requirement defined by image reconstruction quality, this work aims to minimize the total transmit power by jointly optimizing the JSCC encoder-decoder parameters and resource allocation. However, the implicit relationship among JSCC parameters, link quality, and image quality, coupled with the presence of mixed integer-continuous variables, makes the problem difficult…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSatellite Communication Systems · Age of Information Optimization · Error Correcting Code Techniques
