A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015

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Recent research into radio propagation and large-scale channel modeling shows that frequencies can be used above 6 GHz for the new generation of mobile communications (5G). This paper provides a detailed account of measurement campaigns that use directional horn antennas in co-polarization (V-V and H-H) and cross-polarization (V-H) in line-of-sight (LOS) and obstructed-line-of-sight situations between the transmitter and receptor; they were carried out in a corridor and computer laboratory located at the Federal University of Para (UFPA). The measurement data were used to adjust path loss prediction models of radio propagation, through the minimum mean square error (MMSE) method, for indoor environments in the frequencies of 8-11 GHz. The parameters for the models that were determined are as follows: path loss exponent, polarization exponent (co-and cross-polarization), effects of shadowing and path loss exponent for wall losses. Standard deviation and standard deviation point by point are included as statistical metrics. The approximations with regard to the large-scale path loss models for frequencies of 8-11 GHz show a convergence with the measured data, owing to the method employed for the optimization of the MMSE to determine the parameters of the model.

The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where there is a great diversity of scenery and climates. This article proposes an outdoor empirical radio propagation model for Ultra High Frequency (UHF) band, that estimates received power values that can be applied to non-homogeneous paths and different climates, this last being of an innovative character for the UHF band. Different artificial intelligence techniques were chosen on a theoretical and computational basis and made it possible to introduce, organize and describe quantitative and qualitative data quickly and efficiently, and thus determine the received power in a wide range of settings and climates. The proposed model was applied to a city in the Amazon region with heterogeneous paths, wooded urban areas and fractions of freshwater among other factors. Measurement campaigns were conducted to obtain data signals from two digital TV stations in the metropolitan area of the city of Belém, in the State of Pará, to design, compare and validate the model. The results are consistent since the model shows a clear difference between the two seasons of the studied year and small RMS errors in all the cases studied.

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Derived from an early National Bureau of Standards (NBS) tropospheric transhorizon propaption data base [I), a particular loss term defined as path attenuation was used in the radar equation to estimate the behavior of signal-to-noise ratio with frequency (10 to 1000 MHz) and distance (SO to 1000 km) including median and I, 10, 90, 99 percent variability. This loss term depends on frequency, distance, climate, r~fractivity and an empirically derived attenuation function which takes into account effects of antenna heights. Equivalent antenna temperatures are assumed to be due to plactic noise. Receiver noise is characterized by noise figure. For conveniently chosen system parameters (I MW transmitter power, I Hz receiver bandwidth, antenn;~ gains G, = G, = 1000), signal-to-noise ratio behavior is illustrated for several target cross sections (e.g. resonant dipole, conducting sphere) as a function of frequency, distance, variability for particular climates. Conversion to other system parameter values is straightforward. The complete details are available from the author [2].

The feasible choice of a propagation model for a given wireless system depends on environment type among other factors. Thus, it is a crucial decision on radio network planning. This current proposal is a new methodology applied for LTE systems that includes: to find optimal parameters of a propagation model that minimizes Root Mean Square Error (RMSE) and maximizes Grey Relation Grade and Mean Absolute Percentage Error, (GRG-MAPE) in a city-forest environment through the use of metaheuristic optimization such as Cuckoo Search (CS). The results, quantitatively analyzed by RMSE and GRG-MAPE, show a better accuracy of optimized model in comparison with the original version and even with Stanford University Interim (SUI) model.

In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network (GRNN) with the Multiobjective Bat Algorithm (MOBA), for the design and synthesis of the Frequency Selective Surfaces (FSS), aiming its application in data communication systems by diffusion of millimeter waves, specifically, in the IEEE 802.15.3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40.0 GHz at 70.0 GHz, i.e., 30.0 GHz bandwidth and 60.0 GHz resonance. The upper and lower cutoff frequencies, referring to the transmission coefficient's scattering matrix (dB), were obtained at the cutoff threshold at-10dB, to control the bandwidth of the device.