- -

On the Integration of Reconfigurable Intelligent Surfaces in Real-World Environments: A Convenient Approach for Estimation Reflection and Transmission.

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

On the Integration of Reconfigurable Intelligent Surfaces in Real-World Environments: A Convenient Approach for Estimation Reflection and Transmission.

Mostrar el registro completo del ítem

Diaz Rubio, A.; Kosulnikov, S.; Tretyakov, S. (2022). On the Integration of Reconfigurable Intelligent Surfaces in Real-World Environments: A Convenient Approach for Estimation Reflection and Transmission. IEEE Antennas and Propagation Magazine. 64(4):85-95. https://doi.org/10.1109/MAP.2022.3169396

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/195207

Ficheros en el ítem

Metadatos del ítem

Título: On the Integration of Reconfigurable Intelligent Surfaces in Real-World Environments: A Convenient Approach for Estimation Reflection and Transmission.
Autor: Diaz Rubio, Ana Kosulnikov, Sergei Tretyakov, Sergei
Entidad UPV: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Fecha difusión:
Resumen:
[EN] The use of reconfigurable intelligent surfaces (RISs) foroptimization of propagation channels is one of the most promising and revolutionizing techniques for improving efficiency of the next generation of communications ...[+]
Palabras clave: Metasurfaces , Reflection , Scattering , Lighting , Reflector antennas , Reflection coefficient , Phased arrays
Derechos de uso: Cerrado
Fuente:
IEEE Antennas and Propagation Magazine. (issn: 1045-9243 )
DOI: 10.1109/MAP.2022.3169396
Editorial:
Institute of Electrical and Electronics Engineers
Versión del editor: https://doi.org/10.1109/MAP.2022.3169396
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/871464/EU
info:eu-repo/grantAgreement/AKA//330957/
info:eu-repo/grantAgreement/AKA//345178/
info:eu-repo/grantAgreement/MEFP//BG20%2F00024/
Agradecimientos:
This work was supported in part by the European Commission through the Horizon 2020 Artificial Intelligence Aided D-band Network for 5G Long Term Evolution (ARIADNE) project under grant 871464, by the Academy of Finland ...[+]
Tipo: Artículo

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem