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arXiv · 2606.29052

Importance-Aware Resource Allocation for Collaborative Task-Oriented Semantic Communication

Kaiyi Lei·Yuanzhe Peng·Letian Zhang·Jie Xu
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Abstract

Task-oriented semantic communication must allocate scarce radio resources to semantic features under fast fading wireless conditions and strict end-to-end latency budgets. Existing solutions are either optimization-heavy, leading to prohibitive computational overhead during online operation, or rely on end-to-end retraining procedures together with slowly varying channel assumptions. We propose iCoTASC (importance-aware Collaborative Task-Oriented Semantic Communication), a hybrid offline-online framework designed for collaborative multi-device semantic communication systems. iCoTASC leverages attribution-based importance to guide per-dimension embedding selection as a practical communication control signal, models diminishing semantic returns of quantization through a data-driven utility function, and precomputes per-transmitter utility lookup tables offline, which together enable lightweight online scheduling via table lookup and low-complexity refinement under time-varying channels. The proposed framework supports real-time, channel-adaptive semantic resource allocation in distributed systems without requiring retraining of the underlying task inference model.

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Kaiyi Lei, Yuanzhe Peng, Letian Zhang, Jie Xu. 2026-06-27. Importance-Aware Resource Allocation for Collaborative Task-Oriented Semantic Communication. https://arxiv.org/abs/2606.29052

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