Electric Semantic Short Packet Communication: A Green ISAC Perspective
Liao, Haijun Che, Wenxuan Zhou, Zhenyu Wang, Xiaoyan Ali, Aqsa Guizani, Mohsen
Liao, Haijun
Che, Wenxuan
Zhou, Zhenyu
Wang, Xiaoyan
Ali, Aqsa
Guizani, Mohsen
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Department
Machine Learning
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Conference proceeding
Date
2025
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English
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Abstract
Millisecond-precision measurement of smart grid presents elevated demands for 6G sensing and communication capabilities. How to ensure timely, reliable, and green delivery of critical information remains a core challenge. In this paper, we address this issue by studying electric semantic short packet communication from a green integrated sensing and communication (ISAC) perspective. First, a novel information timeliness metric named peak age of incorrect semantics (PAoIS) is developed. It describes the entire lifetime of sensing, compression, encoding, transmission, and decoding. Then, a collaborative problem is formulated to jointly minimize PAoIS and ISAC energy consumption by optimizing sensing frequency and semantic compression ratio. An electric multimodal driven green collaborative optimization algorithm is proposed. It enables dynamical adjustment of sampling ratio of electric multimodal experience samples, enhancing optimization performance under sparse modes. Simulation results verify the effectiveness of the proposed algorithm.
Citation
H. Liao, W. Che, Z. Zhou, X. Wang, A. Ali and M. Guizani, "Electric Semantic Short Packet Communication: A Green ISAC Perspective," ICC 2025 - IEEE International Conference on Communications, Montreal, QC, Canada, 2025, pp. 674-679, doi: 10.1109/ICC52391.2025.11161246.
Source
Proceedings of the ICC 2025-IEEE International Conference on Communications
Conference
ICC 2025-IEEE International Conference on Communications
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ICC 2025-IEEE International Conference on Communications
Publisher
IEEE