References of "Matias, Jose Maria"
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See detailMethod of Rain Attenuation Prediction Based on Long–Short Term Memory Network
Cornejo, Andres; Landeros, Salvador; Matias, Jose Maria et al

in Neural Processing Letters (2022)

Rain attenuation events are one of the foremost drawbacks in satellite communications, impairing satellite link availability. For this reason, it is necessary to foresee rain events to avoid an outage of ... [more ▼]

Rain attenuation events are one of the foremost drawbacks in satellite communications, impairing satellite link availability. For this reason, it is necessary to foresee rain events to avoid an outage of the satellite link. In this paper, we propose and develop a method based on Machine Learning to predict events of rain attenuation without appealing to complex mathematical models. To be specific, we implement a Long–short term memory architecture that is a Deep Learning algorithm based on an artificial recurrent neural network. Furthermore, supervised learning is the learning task for our algorithms. For this purpose, rain attenuation time-series feed the Long–short term memory network at the input to train it. However, the lack of a rainfall database hinders the development of a reliable prediction method. Therefore, we generate a synthetic rain attenuation database by using the recommendations of the International Telecommunication Union. Each model is trained and validated by computational experiments, employing statistical metrics to find the most accurate and reliable models. Thus, the accuracy metric compares the outcomes of the proposal with other related methods and models. As a result, our best model reaches an accuracy of 91.88% versus 87.99% from the external best model, demonstrating superiority over other models/methods. On average, our proposal accuracy reaches a value of 88.08%. Finally, we find out that this proposal can contribute efficiently to improving the performance of satellite system networks by re-routing data traffic or increasing link availabilities, taking advantage of the prediction of rain attenuation events. [less ▲]

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See detailLaboratory Tests of ATSC M/H Commercial Receivers Performance on SFN Networks
Matias, Jose Maria; Ortiz Gomez, Flor de Guadalupe UL; Hernandez, Mario et al

in IEEE Latin America Transactions (2020), 18(10),

The Single Frequency Networks (SFN) are widely used in Digital Television transmission networks due to the high spectral efficiency achieved by them. Digital modulation techniques with a cyclic prefix ... [more ▼]

The Single Frequency Networks (SFN) are widely used in Digital Television transmission networks due to the high spectral efficiency achieved by them. Digital modulation techniques with a cyclic prefix, like OFDM (Orthogonal Frequency Division Multiplex) are adequate to define and use SFN networks due to their ability to deal with the artificial multipath produced in a SFN network. Nevertheless, the ATSC 1.0 and ATSC M/H standards use the VSB-8 modulation technique, which has no cyclic prefix, so it is very sensitive to multipath. The ATSC 1.0 standard has been recently implemented in Mexico, so the ATSC M/H standard can be used in the next years because it is compatible with ATSC 1.0, meanwhile ATSC 3.0, the newest standard of ATSC, it is not compatible.The performance of the reception with VSB-8 modulation depends strongly on the receiver channel equalizer. For this reason, the objective of this study is to analyze the performance of ATSC M/H commercial receivers in SFN networks. The results of this study will help in the implementation of SFN networks in Mexico and other countries that use ATSC 1.0 and ATSC M/H. [less ▲]

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