Autor segons l'article: Casino F; Lopez-Iturri P; Aguirre E; Azpilicueta L; Falcone F; Solanas A
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: Casino Cembellín, Francisco José / Solanas Gómez, Agustín
Paraules clau: Wireless channel Pattern recognition Neural-network Model Framework Collaborative filtering 3-d ray launching
Resum: © 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 2169-3536
Adreça de correu electrònic de l'autor: franciscojose.casino@urv.cat agusti.solanas@urv.cat
Identificador de l'autor: 0000-0003-4296-2876 0000-0002-4881-6215
Data d'alta del registre: 2023-02-19
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://ieeexplore.ieee.org/document/9085406
URL Document de llicència: http://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Ieee Access. 8 83070-83080
Referència 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 de l'article: 10.1109/ACCESS.2020.2992033
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2020
Tipus de publicació: Journal Publications
Repositori URV