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2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020(1)
9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018(1)
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scopus(9)
BLER performance evaluation of an enhanced channel autoencoder
ArticleAbstract: The concept of using autoencoders (AEs) to represent wireless communication systems as an end-to-endPalabras claves:Autoencoder, deep learning, End-to-end learning, modulation, neural network, Wireless communicationsAutores:Lim W., Manuel Eugenio Morocho-Cayamcela, Njoku J.N.Fuentes:scopusBreaking Wireless Propagation Environmental Uncertainty with Deep Learning
ArticleAbstract: Wireless propagation loss modeling has gained significant attention due to its critical importance iPalabras claves:deep learning, image segmentation, Path loss, Propagation model, Wireless CommunicationAutores:Lim W., Maier M., Manuel Eugenio Morocho-CayamcelaFuentes:scopusAn artificially structured step-index metasurface for 10GHz leaky waveguides and antennas
Conference ObjectAbstract: Metasurfaces can be engineered to guide surface waves in a homogeneous path, where sub-wavelength siPalabras claves:antenna, high impedance surface, leaky-lave, Metasurface, Surface wavesAutores:Angsanto S., Caliwag A., Lim W., Manuel Eugenio Morocho-CayamcelaFuentes:scopusAccelerating wireless channel autoencoders for short coherence-time communications
ArticleAbstract: Traditional wireless communication theory is based on complex probabilistic models and fixed conjectPalabras claves:Autoencoders, Channel estimation, deep learning, physical layer, Wireless systemsAutores:Lim W., Manuel Eugenio Morocho-CayamcelaFuentes:scopusArtificial Intelligence in 5G Technology: A Survey
Conference ObjectAbstract: A fully operative and efficient 5G network cannot be complete without the inclusion of artificial inPalabras claves:5g networks, Artificial Intelligence, deep learning, IT Convergence, Machine learning, Next Generation NetworkAutores:Lim W., Manuel Eugenio Morocho-CayamcelaFuentes:scopusMachine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions
ArticleAbstract: Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be a key enablPalabras claves:5G mobile communication, Artificial Intelligence, B5G, Machine learning, Mobile Communication, Wireless CommunicationAutores:Lee H., Lim W., Manuel Eugenio Morocho-CayamcelaFuentes:scopusLateral confinement of high-impedance surface-waves through reinforcement learning
ArticleAbstract: The authors present a model-free policy-based reinforcement learning model that introduces perturbatPalabras claves:Autores:Lim W., Manuel Eugenio Morocho-CayamcelaFuentes:scopusLearning to Communicate with Autoencoders: Rethinking Wireless Systems with Deep Learning
Conference ObjectAbstract: The design and implementation of conventional communication systems are based on strong probabilistiPalabras claves:Autoencoders, Channel estimation, deep learning, physical layer, Wireless systemsAutores:Lim W., Manuel Eugenio Morocho-Cayamcela, Njoku J.N., Park J.Fuentes:scopusPredicting target data rates for dynamic spectrum allocation using Gaussian process regression
ArticleAbstract: Issues in spectrum allocation between wireless network users have arisen due to the fast increase inPalabras claves:Gaussian process regression, Machine learning, Spectrum allocation, Target data rateAutores:Caliwag A., Lim W., Manuel Eugenio Morocho-Cayamcela, Njoku J.N., Xiao P.Fuentes:scopus