Artículo
Combining Software-Defined Radio Learning Modules and Neural Networks for Teaching Communication Systems Courses †
Autor/es | Camuñas Mesa, Luis Alejandro
Rosa Utrera, José Manuel de la |
Departamento | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo |
Fecha de publicación | 2023 |
Fecha de depósito | 2024-02-16 |
Publicado en |
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Resumen | The paradigm known as Cognitive Radio (CR) proposes a continuous sensing of the electromagnetic spectrum in order to dynamically modify transmission parameters, making intelligent use of the environment by taking advantage ... The paradigm known as Cognitive Radio (CR) proposes a continuous sensing of the electromagnetic spectrum in order to dynamically modify transmission parameters, making intelligent use of the environment by taking advantage of different techniques such as Neural Networks. This paradigm is becoming especially relevant due to the congestion in the spectrum produced by increasing numbers of IoT (Internet of Things) devices. Nowadays, many different Software-Defined Radio (SDR) platforms provide tools to implement CR systems in a teaching laboratory environment. Within the framework of a ‘Communication Systems’ course, this paper presents a methodology for learning the fundamentals of radio transmitters and receivers in combination with Convolutional Neural Networks (CNNs). |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía European Union (UE) |
Identificador del proyecto | PID2019-103876RB-I00
PID2022-138078OB-I00 PID2019-105556GB-C31 P20-00599 |
Cita | Camuñas Mesa, L.A. y Rosa Utrera, J.M.d.l. (2023). Combining Software-Defined Radio Learning Modules and Neural Networks for Teaching Communication Systems Courses †. Information (Switzerland), 14 (11), 599. https://doi.org/10.3390/info14110599. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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Combining Software-Defined.pdf | 19.04Mb | [PDF] | Ver/ | |