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Deep Learning-based Transmitter identification on the physical layer

Cyrille Morin 1 Leonardo Cardoso 1 Jakob Hoydis 2 Jean-Marie Gorce 1
1 MARACAS - Modèle et algorithmes pour des systèmes de communication fiables
CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Grenoble - Rhône-Alpes
2 Nokia Bell Labs [Paris-Saclay]
Abstract : An essential part of most wireless communications systems is the identification of a transmitter by a receiver. Being able to identify a transmitter at the physical layer gives context to the communication itself, but is also an important building block for more advanced techniques such as physical layer security. It can also be used to reduce overhead
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Preprints, Working Papers, ...
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https://hal.inria.fr/hal-03117090
Contributor : Cyrille Morin <>
Submitted on : Wednesday, January 20, 2021 - 7:10:18 PM
Last modification on : Friday, January 29, 2021 - 10:56:24 AM

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  • HAL Id : hal-03117090, version 1

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Cyrille Morin, Leonardo Cardoso, Jakob Hoydis, Jean-Marie Gorce. Deep Learning-based Transmitter identification on the physical layer. 2020. ⟨hal-03117090⟩

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