GNConvNet: a group normalization convolutional neural network for robust and secure channel estimation in next-generation OFDM systems

Summary

GNConvNet is a compact fully-convolutional channel estimator for OFDM systems that replaces Batch Normalization with Group Normalization and trains with a teacher-student defensive distillation framework. On a 512-realisation MATLAB 5G Toolbox dataset, it achieves a 13.1% total mean-MSE reduction over the BN baseline across 15 matched-seed trials and yields 5 to 58 times lower malicious MSE under FGSM, BIM, MIM and PGD attacks at epsilon 3.0.

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