Browsing by Author "Ávila Campos, Pablo Esteban"

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Artificial neural network performance evaluation for a hybrid power domain orthogonal/non-orthogonal multiple access (OMA/NOMA) system
(Association for Computing Machinery, Inc, 2020) Belesaca Mendieta, Juan Diego; Ávila Campos, Pablo Esteban; Vázquez Rodas, Andrés Marcelo
Next-generation wireless technologies face considerable challenges in terms of providing the required latency and connectivity for new heterogeneous mobile networks. Driven by these problems, this study focuses on increasing user connectivity together with system throughput. For doing so, we propose and evaluate a hybrid machine learning-driven orthogonal/non-orthogonal multiple access (OMA/NOMA) system. In this work, we use an artificial neural network (ANN) to assign an OMA or NOMA access method to each user equipment (UE). As part of this research we also evaluate the accuracy and training time of the three most relevant learning algorithms of ANN (L-M, BFGS, and OSS). The main objective is to increase the sum-rate of the mobile network in the introduced beamforming and mmWave channel environment. Simulation results show up to a $20%$ sum-rate average performance increase of the system using the ANN management in contrast to a random non-ANN managed system. The Leveberg-Marquard (L-M) training algorithm is the best overall algorithm for this proposed application as presents the highest accuracy of around $77%$ despite 37 minutes of training and lower accuracy of $73%$ with approximately 28 seconds of training time.
Evaluation of LoRaWAN transmission range for wireless sensor networks in riparian forests.
(Association for Computing Machinery, Incacmhelp@acm.org, 2019) Ávila Campos, Pablo Esteban; Araujo Pacheco, Alcides Fabián; Vázquez Rodas, Andrés Marcelo; Astudillo Salinas, Darwin Fabián
© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. Low power wide area networks (LPWAN) such as long range wide area networks (LoRaWAN), provide several advantages on monitoring systems development in forested environments due to its simple set-up, low cost, low power consumption, and wide coverage. Regarding the coverage area, the transmission in forested environments can be highly attenuated by foliage and must be defined to optimize the number of nodes. This paper discusses an empirical study of LoRa with LoRaWAN transmission range in riparian forests, based on path-loss modeling, using both received signal strength indicator (RSSI) and signal-to-noise-ratio (SNR). The measurements have been conducted in the riparian forest of three local rivers at urban, semi-urban, and rural environments located in the city of Cuenca, Ecuador. The measurement results found that there is a significant distribution difference among measurement places, a high correlation between two banks of the same river, a higher standard deviation in urban measurements and a larger coverage in rural areas.