<ul><li>Researchers propose a novel approach to channel estimation in wireless communications using infinite width convolutional networks.</li><li>The traditional channel estimation problem in OFDM systems relies on sparse pilot data, which poses an ill-posed inverse problem.</li><li>The proposed approach uses a convolutional neural tangent kernel (CNTK) derived from an infinitely wide convolutional network, which can accurately estimate the channels with limited training data.</li><li>Numerical results show that the proposed strategy outperforms deep learning methods in terms of speed, accuracy, and computational resources for channel estimation.</li></ul>

Channel Estimation by Infinite Width Convolutional Networks

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