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A Stacked-Autoencoder Based End-To-End Learning Framework For Decode-And-Forward Relay Networks

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IEEE ICASSP 2020 Virtual Conference May 2020

In this work, we study an end-to-end deep learning (DL)-based constellation design for decode-and-forward (DF) relay network. Firstly, we study both the one-way (OW) and two-way (TW) relaying by interpreting DF relay networks as stacked autoencoders, unde

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A Stacked-Autoencoder Based End-To-End Learning Framework For Decode-And-Forward Relay Networks

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In this work, we study an end-to-end deep learning (DL)-based constellation design for decode-and-forward (DF) relay network. Firstly, we study both the one-way (OW) and two-way (TW) relaying by interpreting DF relay networks as stacked autoencoders, unde