dor_id: 4129865

506.#.#.a: Público

590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation

561.#.#.u: https://www.icat.unam.mx/

650.#.4.x: Ingenierías

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: https://revistas.unam.mx/catalogo/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

883.#.#.q: Dirección General de Publicaciones y Fomento Editorial

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/1582/811

100.1.#.a: Perarasi, T.; Moses, M. Leeban; Raju, C.

524.#.#.a: Perarasi, T., et al. (2021). Energy optimization by green sensing methodology for channel design in a cognitive radio network. Journal of Applied Research and Technology; Vol. 19 Núm. 2, 2021; 153-162. Recuperado de https://repositorio.unam.mx/contenidos/4129865

245.1.0.a: Energy optimization by green sensing methodology for channel design in a cognitive radio network

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2021

264.#.1.c: 2021-04-30

653.#.#.a: Green spectrum sensing; fusion rule; voting rule; control channel; energy optimization; cognitive radio network

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/1582

001.#.#.#: 074.oai:ojs2.localhost:article/1582

041.#.7.h: eng

520.3.#.a: An inventive innovation for access of underutilized spectrum and unused range is cognitive radio (CR). Spectrum sensing is the capacity of a gadget to effectively detect the environment and to extricate data from utilizing its radio. A CR framework utilizing hypothesis testing channel banks and the enhancement of the range detecting limit for the predefined requirements on probabilities of missed discovery and of the false alert are proposed to optimize the energy in the system. The limit is additionally upgraded to limit the range detecting mistake subject to the predetermined limitations. The regions of convergence for different estimations of clients are found, and furthermore, the absolute error rate has been broken down for different number of clients going from 1 to 10 and has supported the upgraded estimation of range detecting with least vitality misfortune. The exhibition of a helpful range detecting by different voting standard like OR, AND and M out of N voting rule are applied. From the outcomes, it is seen that the proposed conspire displays exceptionally least impedance for the essential clients. Wastage of energy is limited in the system which characterizes the term green sensing.

773.1.#.t: Journal of Applied Research and Technology; Vol. 19 Núm. 2 (2021); 153-162

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

300.#.#.a: Páginas: 153-162

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.22201/icat.24486736e.2021.19.2.1582

harvesting_date: 2023-11-08 13:10:00.0

856.#.0.q: application/pdf

file_creation_date: 2021-04-22 21:31:51.0

file_modification_date: 2021-04-22 21:32:46.0

file_creator: Yolanda G.G.

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last_modified: 2024-03-19 14:00:00

license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es

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