A simple electromagnetic model for understanding the operation of a MIMO system

Recent years have witnessed intense research in multiple input multiple output (MIMO) wireless communications systems, which use multiple element antennas (MEA) for signal transmission and reception. In this paper, we have described a novel electromagnetic model to investigate the effect of mutual coupling, inter-element spacing and array geometry on the capacity of MIMO systems. Simulation results have been presented illustrating the application of the proposed model. The presented model concept stems from a hollow waveguide analogue. Using this model other aspects such as richness of scattering environment (spacing and clustering), the effect of hard versus soft scatterers and pin hole effect can be investigated.

Data Mining for Browsing Patterns in Weblog Data by Art Neural Networks

Categorising visitors based on their interaction with a website is a key problem in Web content usage. The clickstreams generated by various users often follow distinct patterns, the knowledge of which may help in providing customised content. This paper proposes an approach to clustering weblog data, based on ART2 neural networks. Due to the characteristics of the ART2 neural network model, the proposed approach can be used for unsupervised and self-learning data mining, which makes it adaptable to dynamically changing websites.

On-body characterization of planar differential antennas for multiple, wide, and narrow bands

This paper reports the results of the on-body experimental tests of a set of four planar differential antennas, originated by design variations of radiating elements with the same shape and characterized by the potential for covering wide and narrow bands. All the antenna designs have been implemented on low-cost FR4 substrate and characterized experimentally through on-body measurements. The results show the impact of the proximity to the human body on antenna performance and the opportunities in terms of potential coverage of wide and narrow bands for future ad hoc designs and implementations through wearable substrates targeting on-body and off-body communication and sensing applications.

40 K Liquid Neon Energy Storage Unit

A thermal Energy Storage Unit (ESU) could be used to attenuate inherent temperature fluctuations of a cold finger, either from a cryocooler working or due to sudden income heat bursts. An ESU directly coupled to the cold source acts as a thermal buffer temporarily increasing its cooling capacity and providing a better thermal stability of the cold finger (“Power Booster mode”). The energy storage units presented here use an enthalpy reservoir based on the high latent heat of the liquid-vapour transition of neon in the temperature range 38 - 44 K to store up to 900 J, and that uses a 6 liters expansion volume at RT in order to work as a closed system. Experimental results in the power booster mode will be described: in this case, the liquid neon cell was directly coupled to the cold finger of the working cryocooler, its volume (12 cm3) allowing it to store 450 J at around 40 K. 10 W heat bursts were applied, leading to liquid evaporation, with quite reduced temperature changes. The liquid neon reservoir can also work as a temporary cold source to be used after stopping the cryocooler, allowing for a vibration-free environment. In this case the enthalpy reservoir implemented (24 cm3) was linked to the cryocooler cold finger through a gas gap heat switch for thermal coupling/decoupling of the cold finger. We will show that, by controlling the enthalpy reservoir’s pressure, 900 J can be stored at a constant temperature of 40 K as in a triple-point ESU.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

High-SNR analytical performance of spatial multiplexing MIMO systems with CSI

In this paper, we investigate the average andoutage performance of spatial multiplexing multiple-input multiple-output (MIMO) systems with channel state information at both sides of the link. Such systems result, for example, from exploiting the channel eigenmodes in multiantenna systems. Dueto the complexity of obtaining the exact expression for the average bit error rate (BER) and the outage probability, we deriveapproximations in the high signal-to-noise ratio (SNR) regime assuming an uncorrelated Rayleigh flat-fading channel. Moreexactly, capitalizing on previous work by Wang and Giannakis, the average BER and outage probability versus SNR curves ofspatial multiplexing MIMO systems are characterized in terms of two key parameters: the array gain and the diversity gain. Finally, these results are applied to analyze the performance of a variety of linear MIMO transceiver designs available in the literature.

Vaiheohjatut antenniryhmät GSM-tukiasemissa

Diplomityön aiheena oli selvittää onko Suomessa GSM-tukiasemissa käytössä vaiheohjattuja antenniryhmiäja olisiko tällaisten antennien käyttöön kiinnostusta tai mitään es-teitä. Lähtökohtana tälle työlle oli ajatus GSM-tukiasema-antennista, jota voitaisiin kääntää tarpeen mukaan haluttuun suuntaan. Vaiheohjatut antenniryhmät mahdollistavat juuri tällaisen antennin keilan kääntämisen ja muokkaamisen elektronisesti, ilman kuluvia osia. Keilan muitakin ominaisuuksia voidaan säätää, kuten muotoa ja keilojen määrää. Nämä ominaisuudet mahdollistaisivat esimerkiksi ruuhkaisilla alueilla keilojen lisäämisen, jolloin alueen puhelujen välityskapasiteetti kasvaisi.Tarvittaessa voitaisiin myös keilan muotoa muuttaa. Esimerkiksi hätätilanteessasaadaan haluttu keila suunnattua tarkasti tietylle alueelle tai toiselle tukiasemalle ja näin varmistettua kuuluvuus. Myös huoltotoimenpiteet joissakin tapauksissa helpottuisivat. Etenkin vaikeakulkuisissa paikoissa sijaitsevien tukiasemien ensiapu, esimerkiksi antennin fyysisesti kääntyessä, voitaisiin hoitaa etänä kääntämällä pelkkää keilaa ja tässä tapauksessa kääntää antenni tukiaseman normaalin huollon yhteydessä. Suurimpia ongelmakohtia kyseisen tekniikan käyttöönotossa on ollut hinta, mutta muun muassa uusien valmistustekniikoiden avulla vaiheohjattujen antenniryhmien hintoja ollaan saatu pudotettua.

Implementation of a Neural Network Classifier for Noise Sources in the Ocean

The paper investigates the feasibility of implementing an intelligent classifier for noise sources in the ocean, with the help of artificial neural networks, using higher order spectral features. Non-linear interactions between the component frequencies of the noise data can give rise to certain phase relations called Quadratic Phase Coupling (QPC), which cannot be characterized by power spectral analysis. However, bispectral analysis, which is a higher order estimation technique, can reveal the presence of such phase couplings and provide a measure to quantify such couplings. A feed forward neural network has been trained and validated with higher order spectral features

Otimização do controle eletrônico do diagrama de radiação de arranjos de antenas usando algoritmos genéticos com codificação real

Antenna arrays are able to provide high and controlled directivity, which are suitable for radiobase stations, radar systems, and point-to-point or satellite links. The optimization of an array design is usually a hard task because of the non-linear characteristic of multiobjective, requiring the application of numerical techniques, such as genetic algorithms. Therefore, in order to optimize the electronic control of the antenna array radiation pattem through genetic algorithms in real codification, it was developed a numerical tool which is able to positioning the array major lobe, reducing the side lobe levels, canceling interference signals in specific directions of arrival, and improving the antenna radiation performance. This was accomplished by using antenna theory concepts and optimization methods, mainly genetic algorithms ones, allowing to develop a numerical tool with creative genes codification and crossover rules, which is one of the most important contribution of this work. The efficiency of the developed genetic algorithm tool is tested and validated in several antenna and propagation applications. 11 was observed that the numerical results attend the specific requirements, showing the developed tool ability and capacity to handle the considered problems, as well as a great perspective for application in future works.

Asymmetrical magnetization in three-phase core type transformers

The performance of the three-phase core type transformers, under AC/DC double excitation is discussed in this work. It is presented a mathematical model that considers the mutual coupling between phases and the magnetic nonlinearity. The validity of the proposed model is verified by means of the experimental and simulated results.

Um modelo para condutores múltiplos considerando a distribuição da corrente nos subcondutores

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Using Universal Line Model (ULM) for Representing Electromagnetic Transients in Three-Phase Transmission Lines

The second-order differential equations that describe the polyphase transmission line are difficult to solve due to the mutual coupling among them and the fact that the parameters are distributed along their length. A method for the analysis of polyphase systems is the technique that decouples their phases. Thus, a system that has n phases coupled can be represented by n decoupled single-phase systems which are mathematically identical to the original system. Once obtained the n-phase circuit, it's possible to calculate the voltages and currents at any point on the line using computational methods. The Universal Line Model (ULM) transforms the differential equations in the time domain to algebraic equations in the frequency domain, solve them and obtain the solution in the frequency domain using the inverse Laplace transform. This work will analyze the method of modal decomposition in a three-phase transmission line for the evaluation of voltages and currents of the line during the energizing process.

Analysis of Structural Integrity Using an ARTMAP-Fuzzy Artificial Neural Network

This paper presents the application of artificial neural networks in the analysis of the structural integrity of a building. The main objective is to apply an artificial neural network based on adaptive resonance theory, called ARTMAP-Fuzzy neural network and apply it to the identification and characterization of structural failure. This methodology can help professionals in the inspection of structures, to identify and characterize flaws in order to conduct preventative maintenance to ensure the integrity of the structure and decision-making. In order to validate the methodology was modeled a building of two walk, and from this model were simulated various situations (base-line condition and improper conditions), resulting in a database of signs, which were used as input data for ARTMAP-Fuzzy network. The results show efficiency, robustness and accuracy.

Transmissão indutiva de energia eletromagnética sem fios, para aplicações em postos de abastecimento de veículos elétricos puros: modelação para o elemento eletromagnético

Pós-graduação em Engenharia Elétrica - FEIS

Influence of double excitation AC/DC in the reactive power demand of 3-phase transformers

In this work it is discussed the performance of the reactive power demand in three-leg transformer core and three-phase transformer bank, under different conditions of AC/DC double excitation. In order to analyse the influence of double excitation in reactive power theoretically a mathematical model was developed considering the mutual coupling between phases and the magnetic nonlinearity. The validity of the proposed model is verified by means of the experimental and simulated results.