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20242026
most citedInterpreting Deep Neural Network-Based Receiver Under Varying Signal-To-Noise Ratios

1 citations · 1 across the 5 of their papers we have counts for

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eess.SP2025

Demonstrating Interoperable Channel State Feedback Compression with Machine Learning

Dani Korpi, Rachel Wang, Jerry Wang +20

Neural network-based compression and decompression of channel state feedback has been one of the most widely studied applications of machine learning (ML) in wireless networks. Var…

cs.LG2025

Out-of-Distribution Detection via Channelwise Feature Aggregation in Neural Network-Based Receivers

Marko Tuononen, Heikki Penttinen, Duy Vu +3

Neural network-based radio receivers are expected to play a key role in future wireless systems, making reliable Out-Of-Distribution (OOD) detection essential. We propose a post-ho…