Percorrer por autor "Cuiñas, Iñigo"
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- Dual-Band Single-Layer Fractal Frequency Selective Surface for 5G ApplicationsPublication . Decoster, Bram; Maes, Stephanie; Cuiñas, Iñigo; Sánchez, Manuel García; Caldeirinha, Rafael; Verhaevert, JoDue to the global growth in popularity of Fifth Generation (5G) cellular communications, the demand for shielding against it has risen for a variety of applications, mainly related to cyber-security but also to isolation, calm areas and so on. This research paper aims to provide a suitable dual-band fractal FSS (Frequency Selective Surface) for the 5G lower band frequencies: 750 MHz and 3.5 GHz. The unit cell is in the shape of a bow tie, where each of the triangular parts are Sierpiński triangles. One major addition to the unit cell is a central metal strip to make the manufacturing of the FSS more feasible and to tune the operation frequencies and bandwidths. As with each different stage of a fractal antenna, the different stages of the fractal FSS design behave differently. For this application, stage 2 is sufficient, as we are able to cover frequency bands among those included in the FR1 5G spectrum. Some equations were derived using linear regression in order to provide specific design tools for building an FSS. These equations have high accuracy and can be used to adapt the proposed design to other frequencies. Some other parameters, which are not represented in the aforementioned equations, can also be adjusted for minor tweaking of the final design. This design performs well except under large incidence angles. This should be taken into account when proposing the installation of a structure based on it. A good agreement between simulation and measurement results is observed.
- Dual‐band single‐layer quarter ring frequency selective surface for Wi‐Fi applicationsPublication . Ferreira, David; Cuiñas, Iñigo; Caldeirinha, Rafael; Fernandes, Telmo R.This study proposes a frequency selective surface (FSS) design to be used in Wi‐Fi shielding applications as either a band reject or band pass dual‐band single‐layer filter. The proposed design consists of a combination of basic elements, that is, ring loops/slots, and is tuned at both 2.4 and 5.2 GHz Wi‐Fi frequency bands. It has a relatively stable frequency response in the aforementioned Wi‐Fi bands for incidence angles ranging from 0° to 45°. Both band reject and band pass designs are presented, along with their unit cell dimensions. Simulation and model validation through measurements demonstrate the performance of the proposed FSS design. Active variants are also proposed and briefly evaluated, in simulation environment, which should allow for applications where an on–off switching is desired at 2.4 and 5.2 GHz Wi‐Fi bands.
- Modeling and inferring the attenuation induced by vegetation barriers at 2G/3G/4G cellular bands using Artificial Neural NetworksPublication . Gómez-Pérez, Paula; Crego-García, Marcos; Cuiñas, Iñigo; Caldeirinha, Rafael F. S.Modeling vegetation is a recurrent problem for wireless communications industry. The raising number of available frequency bands increases this issue, since most of the existing methods nowadays rely on measurement campaigns. The presence of vegetation in urban areas (such as parks or gardens) is bothersome for radio planners, which have to deal with an in-excess attenuation difficult to predict due to the large number of different cases (i.e. vegetation species, topologies of vegetation volumes, frequencies. . .). Usually, these vegetation formations appear in the form of forests or barriers, emphasizing the problem, since their impact in the transmitted power is not negligible. This paper proposes the use of Artificial Neural Networks as powerful tools to model and infer the excess attenuation induced by vegetation formations. The study is held at cellular frequency bands (2G/3G/4G) for different vegetation species and barrier configurations, where a multilayer perceptron has been trained over existing experimental data at 2G/3G frequencies. We demonstrate the efficiency of the model to predict accurately the attenuation in the frequencies for which it has been trained for, and to infer and extend the model obtained to new frequencies, e.g. 4G, while maintaining an overall low median error. The proposed framework, which is sought to be a powerful tool for radio planners to predict attenuation due to a vegetation formation, has been validated against measurements conducted in controlled environments at several mobile radio frequencies, but it could be easily extended to other radio frequencies, such as WiFi, WiMax or 5G frequency bands, as long as a proper training is performed, to include different propagation effects at such bands.
- Tunable square slot FSS EC modelling and optimisationPublication . Ferreira, David; Caldeirinha, Rafael Ferreira Silva; Cuiñas, Iñigo; Fernandes, Telmo RuiAn equivalent circuit model for tunable square slot frequency selective surfaces (FSS) is proposed. Tuning is achieved with the inclusion of a discrete capacitance element, at key points within the FSS unit cell. The equivalent circuit model takes into account the FSS physical attributes. The performance of the proposed equivalent circuit model was evaluated against results obtained from appropriate electromagnetic simulations. Results demonstrate the validity of the proposed equivalent circuit model, in which good estimations of the frequency response of FSS structures were obtained. A RMSE value of 190 MHz was extracted from the complete parametric simulation set. The model was further validated against measurements performed on a tunable active FSS prototype inside an anechoic chamber. Tuning of the FSS was achieved by means of bias voltage to modify the varicaps capacitance value. A relatively good agreement was verified between equivalent circuit model, electromagnetic simulations and measurements. Finally, this work is sought to be a useful contribution to the literature on this topic, by improving on the elementary models of such FSS structures and be useful as a good and fast first approach to determine approximate FSS unit cell dimensions.
- Using artificial neural networks to scale and infer vegetation media phase functionsPublication . Gómez-Pérez, Paula; Caldeirinha, Rafael; Fernandes, Telmo, Telmo Rui Carvalhinho Cunha, Telmo R.; Cuiñas, IñigoAccurate vegetation models usually rely on experimental data obtained by means of measurement campaigns. Nowadays, RET and dRET models provide a realistic characterization of vegetation volumes, including not only in-excess attenuation, but also scattering, diffraction and depolarization. Nevertheless, both approaches imply the characterization of the forest media by means of a range of parameters, and thus, the construction of a simple parameter extraction method based on propagation measurements is required. Moreover, when dealing with experimental data, two common problems must be usually overcome: the scaling of the vegetation mass parameters into different dimensions, and the scarce number of frequencies available within the experimental data set. This paper proposes the use of Artificial Neural Networks as accurate and reliable tools able to scale vegetation parameters for varying physical dimensions and to predict them for new frequencies. This proposal provides a RMS error lower than 1 dB when compared to unbiased measured data, leading to an accurate parameter extracting method, while being simple enough for not to increase the computational cost of the model.