Work

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
Language: English
Open Access status: gold
Estimated APC paid: $1,500
OpenAlex ID: W4416420687
FWCI: 1.617
Cites: 36
Cited by: 7
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