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Recent Progress in End-to-End Learning for the Physical Layer

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No logo availableInstitut des Hautes Études Scientifiques (IHÉS)
 Hoydis, Jakob

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Recent Progress in End-to-End Learning for the Physical Layer
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5
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Abstract
End-to-end learning is one of the most promising applications of machine learning for the physical layer of communication systems. I will provide a tutorial introduction to the topic and will discuss recent results as well as future research direction.