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arXiv · 2607.01921

Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access

João Henrique Inacio de Souza·Mattia Merluzzi·Mateus P. Mota·Beatriz Soret·Petar Popovski
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Abstract

Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channel coding and incur high latency under limited spectrum availability and fading channels. To address this, we propose a transmission framework with opportunistic spectrum access, in which the transmitter sends discrete latent representations learned via a vector-quantized variational autoencoder (VQ-VAE) over idle licensed channels using standard digital modulation. The AI-powered receiver is still able to reconstruct task-related information from the heavily compressed data. We develop a cross-layer latency model that accounts for compression, block errors, retransmissions, and stochastic channel access. Results on latency-accuracy trade-offs show that the proposed scheme achieves at least 79- and 3.3-fold latency reductions with only 5.7% and 2.4% drops in classification accuracy compared to benchmarks using conventional source and channel coding. The framework enables low-latency communication and reliable task execution even under limited spectrum availability and challenging channel conditions.

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João Henrique Inacio de Souza, Mattia Merluzzi, Mateus P. Mota, Beatriz Soret, Petar Popovski. 2026-07-02. Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access. https://arxiv.org/abs/2607.01921

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