Feature-importance-aware transmission control in semantic communications
Year: 2025
Type: article
Abstract: Semantic communication shifts the focus from bit-level accuracy to task-relevant meaning. However, most methods assume equal importance across semantic units and rely on costly retraining, limiting scalability. This work proposes an importance-aware framework that accounts for unequal feature contributions. It introduces a new metric, importance-weighted semantic spectral efficiency (wSSE), to prioritize task-relevant features. It develops an empirically derived feature-accuracy matrix, inspired by saturation behavior. The framework enables importance-aware feature selection and subchannel allocation without online learning. This framework targets resource-constrained edge systems such as IoT cameras, UAV detection, and AR/VR. Experiments show up to 73.3% higher efficiency under constrained resources.
Source: ICT Express
Institutions: Chung-Ang University, Hallym University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,500
Awards: G5192399226, G5843789247
OpenAlex ID: W4416420687
