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Mostrando ítems 81-90 de 432
The rayleigh fading channel prediction via deep learning
(Wiley-Hindawi, 2018)
This paper presents a multi-time channel prediction system based on backpropagation (BP) neural network with multi-hidden layers, which can predict channel information effectively and benefit for massive MIMO performance, ...
A Bivariate Kappa-mu Distribution
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCPiscataway, 2016)
A general bivariate Ricean model and its statistics
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2007)
Generalized Nakagami-m phase crossing rate
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2006)
Analytical Approach to Model the Fade Depth and the Fade Margin in UWB Channels
(Facultad de IngenieríaIngeniería TelemáticaDepartamento Académico de Tecnologías de Información y Comunicaciones (TICs), 2010-11-01)
Avaliação de desempenho da codificação wavelet em canais seletivos em frequência
(Universidade Federal do Rio Grande do NorteBRUFRNPrograma de Pós-Graduação em Engenharia ElétricaAutomação e Sistemas; Engenharia de Computação; Telecomunicações, 2014-02-14)
Wavelet coding has emerged as an alternative coding technique to minimize the fading effects of wireless channels. This work evaluates the performance of wavelet coding, in terms of bit error probability, over time-varying, ...
Bivariate Hoyt (Nakagami-q) Distribution
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2012)
Practical, Highly Efficient Algorithm for Generating kappa-mu and eta-mu Variates and a Near-100% Efficient Algorithm for Generating alpha-mu Variates
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2012)