Autor según el artículo: Casino F; Lopez-Iturri P; Aguirre E; Azpilicueta L; Falcone F; Solanas A

Departamento: Enginyeria Informàtica i Matemàtiques

Autor/es de la URV: Casino Cembellín, Francisco José / Solanas Gómez, Agustín

Palabras clave: Wireless channel Pattern recognition Neural-network Model Framework Collaborative filtering 3-d ray launching

Resumen: © 2013 IEEE. In this paper, an enhancement of a hybrid simulation technique based on combining collaborative filtering with deterministic 3D ray launching algorithm is proposed. Our approach implements a new methodology of data depuration from low definition simulations to reduce noisy simulation cells. This is achieved by processing the maximum number of permitted reflections, applying memory based collaborative filtering, using a nearest neighbors' approach. The depuration of the low definition ray launching simulation results consists on discarding the estimated values of the cells reached by a number of rays lower than a set value. Discarded cell values are considered noise due to the high error that they provide comparing them to high definition ray launching simulation results. Thus, applying the collaborative filtering technique both to empty and noisy cells, the overall accuracy of the proposed methodology is improved. Specifically, the size of the data collected from the scenarios was reduced by more than 40% after identifying and extracting noisy/erroneous values. In addition, despite the reduced amount of training samples, the new methodology provides an accuracy gain above 8% when applied to the real-world scenario under test, compared with the original approach. Therefore, the proposed methodology provides more precise results from a low definition dataset, increasing accuracy while exhibiting lower complexity in terms of computation and data storage. The enhanced hybrid method enables the analysis of larger complex scenarios with high transceiver density, providing coverage/capacity estimations in the design of heterogeneous IoT network applications.

Áreas temáticas: Telecommunications Materials science (miscellaneous) Materials science (all) General materials science General engineering General computer science Engineering, electrical & electronic Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Electrical and electronic engineering Computer science, information systems Computer science (miscellaneous) Computer science (all) Ciência da computação

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 2169-3536

Direcció de correo del autor: franciscojose.casino@urv.cat agusti.solanas@urv.cat

Identificador del autor: 0000-0003-4296-2876 0000-0002-4881-6215

Fecha de alta del registro: 2023-02-19

Versión del articulo depositado: info:eu-repo/semantics/publishedVersion

Enlace a la fuente original: https://ieeexplore.ieee.org/document/9085406

URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/

Referencia al articulo segun fuente origial: Ieee Access. 8 83070-83080

Referencia de l'ítem segons les normes APA: Casino F; Lopez-Iturri P; Aguirre E; Azpilicueta L; Falcone F; Solanas A (2020). Enhanced wireless channel estimation through parametric optimization of hybrid ray launching-collaborative filtering technique. Ieee Access, 8(), 83070-83080. DOI: 10.1109/ACCESS.2020.2992033

DOI del artículo: 10.1109/ACCESS.2020.2992033

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2020

Tipo de publicación: Journal Publications