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The Folded Normal Distribution: A New Model for the Small-Scale Fading in Line-of-Sight (LOS) Condition

Authors :
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Agencia Estatal de Investigación
Ministerio de Economía y Competitividad
Reig, Juan
Rodrigo Peñarrocha, Vicent Miquel
Rubio Arjona, Lorenzo
Martínez-Inglés, María T.
Molina-García-Pardo, José María
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Agencia Estatal de Investigación
Ministerio de Economía y Competitividad
Reig, Juan
Rodrigo Peñarrocha, Vicent Miquel
Rubio Arjona, Lorenzo
Martínez-Inglés, María T.
Molina-García-Pardo, José María
Publication Year :
2019

Abstract

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.<br />[EN] In this paper, a novel form of the folded normal (FN) distribution has been proposed to model the small-scale fading in wireless communications. From a multiple-input multiple-output (MIMO) measurement campaign conducted in a lab environment with the line-of-sight (LOS) conditions at both the 60 and the 94 GHz bands, the authors obtain the parameters of the Rician, FN, and kappa-mu distributions. These parameters have been calculated by using the least square (LS) approximation and with techniques of statistical inference. The FN distribution provides the best fitting to the experimental results using the Kolmogorov-Smirnov (K-S) test for the inferred estimators with values of the ful llment of 100% and 69.82% at the 60 and 94 GHz bands, respectively, for a significance level of 1%.

Details

Database :
OAIster
Notes :
TEXT, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1258883387
Document Type :
Electronic Resource