Fast Near-Field Multi-Focusing of Antenna Arrays Including Element Coupling Using Neural Networks

A novel near-field focusing approach based on the use of artificial neural networks (NNs) is proposed. It is able to provide the set of weights or feeding values that must be applied to the elements of an array so that the global radiation/reception pattern is focused on one or more predefined positions in the near environment. Due to the use of a properly trained NN, it is able to work fast enough for real-time applications, such as wireless energy and information transfer where moving devices may require quick adaptation of the radiated field distribution and, hence, of the weights applied to the array. Moreover, the training procedure using examples generated with a convenient electromagnetic analysis tool allows taking into account both the radiation pattern of the elements of the array and the coupling effects between them

Davison, Frederick

URSI International Symposium on Electromagnetic Theory (EMTS) (2019. San Diego)This paper presents the state-of-the-art on the synthesis techniques and technologies of the antennas for short-range radio links, when specific focusing/shaping of the radiated field in one or more regions close to the antenna itself (inside the antenna radiative near-field region) is required

Fast methods for evaluating the electric field level in 2D-indoor environments

When estimating the electric field level in an indoor environment, the usual complexity of the geometry and its large electric size make it necessary to deal with asymptotic assumptions, also known as high frequency techniques. But, even with these assumptions, the computational complexity, and the CPU-time cost, can be very high. Considering this drawback, this paper proposes the implementation of a "Neural Networks System" for fast calculations of the Electric field in 2D-indoor environment

Design of asymptotically optimal improper constellations with hexagonal packing

This paper addresses the problem of designing asymptotically optimal improper constellations with a given circularity coefficient (correlation coefficient between the constellation and its complex conjugate). The designed constellations are optimal in the sense that, at high signal-to-noise-ratio (SNR) and for a large number of symbols, yield the lowest probability of error under an average power constraint for additive white Gaussian noise channels. As the number of symbols grows, the optimal constellation is the intersection of the hexagonal lattice with an ellipse whose eccentricity determines the circularity coefficient. Based on this asymptotic result, we propose an algorithm to design finite improper constellations. The proposed constellations provide significant SNR gains with respect to previous improper designs, which were generated through a widely linear transformation of a standard M-ary quadrature amplitude modulation constellation. As an application example, we study the use of these improper constellations by a secondary user in an underlay cognitive radio network.The work of Jesús A. López-Fernández and R. G. Ayestarán was partly supported by the Ministerio de Ciencia, Innovación y Universidades under project TEC2017-86619-R (ARTEINE), and by the Gobierno del Principado de Asturias under project GRUPIN-IDI2018-000191. The work of I. Santamaria was partly supported by the Ministerio de Economía y Competitividad (MINECO) of Spain, and AEI/FEDER funds of the E.U., under grant TEC2016-75067-C4-4-R (CARMEN) and TEC2015-69648-REDC (Red COMONSENS). The work of C. Lameiro was supported by the German Research Foundation (DFG) under grant LA 4107/1-1

Systematic Framework for Reflectarray Synthesis Based on Phase Optimization

A new systematic synthesis framework for reflectarray antennas is discussed. Optimization based on the Levenberg-Marquardt algorithm is used to obtain the phase distribution of the reflection coefficients required on the reflectarray surface, in order to achieve the pattern specifications. A Local Multipoint Distribution System (LMDS) base station working in the 24.5–26.5 GHz frequency band has been proposed to evaluate the method. The 3D requirements are defined by the combination of the elevation and templates and considering a maximum acceptable ripple in the beam shaping. Some illustrative results are obtained

Simultaneous Synthesis of Arrays for Near Field Focusing and Far Field Constraints

Iberian Meeting on Computational Electromagnetics (12º, 2018, Coimbra

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

Support Vector Regression for the Modeling and Synthesis of Near-Field Focused Antenna Arrays

The powerful support vector regression framework is proposed in a novel method for near-field focusing using antenna arrays. By using this machine-learning method, the set of weights required in the elements of an array can be calculated to achieve an assigned near-field distribution focused on one or more positions. The computational cost is concentrated in an initial training process so that the trained system is fast enough for applications where moving devices are involved. The increased learning capabilities of support vector machines allow using a reduced number of training samples. Thus, these training samples may be generated with a prototype or a convenient electromagnetic analysis tool, and hence realistic effects, such as coupling or the individual radiation patterns of the elements of the arrays, are accounted for. Illustrative examples are presented

Synthesis of near field focused arrays including far field constrains

International Applied-Computational Electromagnetics-Society Symposium (2017. Firenze