Phuc-Thinh Huynh

Deep Spectrum Sensing via Residual One-For-All Group Convolutions and Hierarchical Auxiliary Fusion

The paradigm shift toward sustainable spectrum utilization in future wireless architectures requires spectrum sensing methods that balance fine-grained characterization of complex spectral scenes with minimal computational overhead. To this end, we propose OFA-UNet, a cost-efficient model for segmenting various signals...