dc.contributor.author | Nieto-Chaupis, Huber | |
dc.date.accessioned | 2023-12-28T14:59:26Z | |
dc.date.available | 2023-12-28T14:59:26Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://hdl.handle.net/20.500.13067/2925 | |
dc.description.abstract | The fact that a mobile user moves far away from a fixed antenna base station, can be rise to a stochastic scenarios that are entirely governed by a Bayesian theory. This paper introduces a derivation of the electric field at the mobile station. In addition, the received radiation can be expressed in terms of integer-order Bessel functions. A direct derivation motivates to conclude that wireless channels might be obeying a Bayes statistics in according to the simulations done in this paper. | es_PE |
dc.format | application/pdf | es_PE |
dc.language.iso | eng | es_PE |
dc.publisher | IEEE | es_PE |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_PE |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | es_PE |
dc.subject | Wireless communication | es_PE |
dc.subject | Base stations | es_PE |
dc.subject | Antenna theory | es_PE |
dc.subject | Conferences | es_PE |
dc.subject | Mobile antennas | es_PE |
dc.subject | Bayes methods | es_PE |
dc.subject | Electric fields | es_PE |
dc.title | The Bayesian Approach to Derive Wireless Fields in Mobile Stations | es_PE |
dc.type | info:eu-repo/semantics/article | es_PE |
dc.identifier.journal | 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI) | es_PE |
dc.identifier.doi | https://doi.org/10.1109/USNC-RSI52151.2023.10238215 | |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#2.02.04 | es_PE |
dc.relation.url | https://ieeexplore.ieee.org/document/10238215 | es_PE |