Semantic Enabled 6G LEO Satellite Communication for Earth Observation: A Resource-Constrained Network Optimization
<|reference_start|>Semantic Enabled 6G LEO Satellite Communication for Earth Observation: A Resource-Constrained Network Optimization: Earth observation satellites generate large amounts of real-time data for monitoring and managing time-critical events such as disaster relief missions. This presents a major challenge for satellite-to-ground communications operating under limited bandwidth capacities. This paper explores semantic communication (SC) as a potential alternative to traditional communication methods. The rationality for adopting SC is its inherent ability to reduce communication costs and make spectrum efficient for 6G non-terrestrial networks (6G-NTNs). We focus on the critical satellite imagery downlink communications latency optimization for Earth observation through SC techniques. We formulate the latency minimization problem with SC quality-of-service (SC-QoS) constraints and address this problem with a meta-heuristic discrete whale optimization algorithm (DWOA) and a one-to-one matching game. The proposed approach for captured image processing and transmission includes the integration of joint semantic and channel encoding to ensure downlink sum-rate optimization and latency minimization. Empirical results from experiments demonstrate the efficiency of the proposed framework for latency optimization while preserving high-quality data transmission when compared to baselines.<|reference_end|>
@article{hassan2024semantic,
    title={Semantic Enabled 6G LEO Satellite Communication for Earth Observation: A
  Resource-Constrained Network Optimization},
    author={Sheikh Salman Hassan, Loc X. Nguyen, Yan Kyaw Tun, Zhu Han, and Choong
  Seon Hong},
    journal={arXiv preprint arXiv:2408.03959},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.03959},
    primaryClass={cs.NI eess.SP}
}