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Uncertainty-Aware Multi-Task Learning for Joint Modulation Recognition and SINR Estimation

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Joint modulation recognition and signal-to-interference-plus-noise ratio (SINR) estimation can reduce duplicated processing in intelligent receivers, but the two tasks have different uncertainty characteristics. This letter proposes an uncertainty-aware multi-task model that transforms each short normalized in-phase/quadrature window into 36 deterministic, label-free statistics, learns a shared representation, and uses task-specific adapters for modulation classification and heteroscedastic SINR regression. A joint uncertainty score combines classification entropy and predicted regression vari

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