Classificação Automática de Modulação Digital com uso de Correntropia para Ambientes de Rádio Cognitivo

Modern wireless systems employ adaptive techniques to provide high throughput while observing desired coverage, Quality of Service (QoS) and capacity. An alternative to further enhance data rate is to apply cognitive radio concepts, where a system is able to exploit unused spectrum on existing licensed bands by sensing the spectrum and opportunistically access unused portions. Techniques like Automatic Modulation Classification (AMC) could help or be vital for such scenarios. Usually, AMC implementations rely on some form of signal pre-processing, which may introduce a high computational cost or make assumptions about the received signal which may not hold (e.g. Gaussianity of noise). This work proposes a new method to perform AMC which uses a similarity measure from the Information Theoretic Learning (ITL) framework, known as correntropy coefficient. It is capable of extracting similarity measurements over a pair of random processes using higher order statistics, yielding in better similarity estimations than by using e.g. correlation coefficient. Experiments carried out by means of computer simulation show that the technique proposed in this paper presents a high rate success in classification of digital modulation, even in the presence of additive white gaussian noise (AWGN)

GingaForAll: linha de Produtos do Middleware Ginga

Many challenges have been imposed on the middleware to support applications for digital TV because of the heterogeneity and resource constraints of execution platforms. In this scenario, the middleware must be highly configurable so that it can be customized to meet the requirements of applications and underlying platforms. This work aims to present the GingaForAll, a software product line developed for the Ginga - the middleware of the Brazilian Digital TV (SBTVD). GingaForAll adds the concepts of software product line, aspect orientation and model-driven development to allow: (i) the specification of the common characteristics and variables of the middleware, (ii) the modularization of crosscutting concerns - both mandatory and concepts variables - through aspects, (iii) the expression of concepts as a set of models that increase the level of abstraction and enables management of various software artifacts in terms of configurable models. This work presents the architecture of the software product line that implements such a tool and architecture that supports automatic customization of middleware. The work also presents a tool that implements the process of generating products GingaForAll

Imageamento digital de paleocavernas colapsadas com georadar

In this study, the methodological procedures involved in digital imaging of collapsed paleocaves in tufa using GPR are presented. These carbonate deposits occur in the Quixeré region, Ceará State (NE Brazil), on the western border of the Potiguar Basin. Collapsed paleocaves are exposed along a state road, which were selected to this study. We chose a portion of the called Quixeré outcrop for making a photomosaic and caring out a GPR test section to compare and parameterize the karst geometries on the geophysical line. The results were satisfactory and led to the adoption of criteria for the interpretation of others GPR sections acquired in the region of the Quixeré outcrop. Two grids of GPR lines were acquired; the first one was wider and more spaced and guided the location of the second grid, denser and located in the southern part of the outcrop. The radargrams of the second grid reveal satisfactorily the collapsed paleocaves geometries. For each grid has been developed a digital solid model of the Quixeré outcrop. The first model allows the recognition of the general distribution and location of collapsed paleocaves in tufa deposits, while the second more detailed digital model provides not only the 3D individualization of the major paleocaves, but also the estimation of their respective volumes. The digital solid models are presented here as a new frontier in the study of analog outcrops to reservoirs (for groundwater and hydrocarbon), in which the volumetric parameterization and characterization of geological bodies become essential for composing the databases, which together with petrophysical properties information, are used in more realistic computer simulations for sedimentary reservoirs.