Azpilicueta Fernández de las Heras, Leyre
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Azpilicueta Fernández de las Heras
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Leyre
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Ingeniería Eléctrica, Electrónica y de Comunicación
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ISC. Institute of Smart Cities
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Publication Open Access Performance analysis of ZigBee wireless networks for AAL through hybrid ray launching and collaborative filtering(Hindawi, 2016) López Iturri, Peio; Casino, Fran; Aguirre Gallego, Erik; Azpilicueta Fernández de las Heras, Leyre; Falcone Lanas, Francisco; Solanas, Agustí; Ingeniaritza Elektrikoa eta Elektronikoa; Institute of Smart Cities - ISC; Ingeniería Eléctrica y ElectrónicaThis paper presents a novel hybrid simulation method based on the combination of an in-house developed 3D ray launching algorithm and a collaborative filtering (CF) technique, which will be used to analyze the performance of ZigBee-based wireless sensor networks (WSNs) to enable ambient assisted living (AAL). The combination of Low Definition results obtained by means of a deterministic ray launching method and the application of a CF technique leads to a drastic reduction of the time and computational cost required to obtain accurate simulation results. The paper also reports that this kind of AAL indoor complex scenario withmultiple wireless devices needs a thorough and personalized radioplanning analysis as radiopropagation has a strong dependence on the network topology and the specific morphology of the scenario. The wireless channel analysis performed by our hybrid method provides valuable insight into network design phases of complex wireless systems, typical in AAL-oriented environments.Thus, it results in optimizing network deployment, reducing overall interference levels, and increasing the overall system performance in terms of cost reduction, transmission rates, and energy efficiency.Publication Open Access Enhanced wireless channel estimation through parametric optimization of hybrid ray launching-collaborative filtering technique(IEEE, 2020) Casino, Fran; López Iturri, Peio; Aguirre Gallego, Erik; Azpilicueta Fernández de las Heras, Leyre; Falcone Lanas, Francisco; Solanas, Agustí; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de ComunicaciónIn this paper, an enhancement of a hybrid simulation technique based on combining collaborative filtering with deterministic 3D ray launching algorithm is proposed. Our approach implements a new methodology of data depuration from low definition simulations to reduce noisy simulation cells. This is achieved by processing the maximum number of permitted reflections, applying memory based collaborative filtering, using a nearest neighbors' approach. The depuration of the low definition ray launching simulation results consists on discarding the estimated values of the cells reached by a number of rays lower than a set value. Discarded cell values are considered noise due to the high error that they provide comparing them to high definition ray launching simulation results. Thus, applying the collaborative filtering technique both to empty and noisy cells, the overall accuracy of the proposed methodology is improved. Specifically, the size of the data collected from the scenarios was reduced by more than 40% after identifying and extracting noisy/erroneous values. In addition, despite the reduced amount of training samples, the new methodology provides an accuracy gain above 8% when applied to the real-world scenario under test, compared with the original approach. Therefore, the proposed methodology provides more precise results from a low definition dataset, increasing accuracy while exhibiting lower complexity in terms of computation and data storage. The enhanced hybrid method enables the analysis of larger complex scenarios with high transceiver density, providing coverage/capacity estimations in the design of heterogeneous IoT network applications.