Análise técnica dos principais índices bolsistas europeus

Mestrado em Controlo e Gestão e dos Negócios

Improving accuracy for OTD based 3G geolocation in real urban/suburban environments

This paper presents the recent research results about the development of a Observed Time Difference (OTD) based geolocation algorithm based on network trace data, for a real Universal Mobile Telecommunication System (UMTS) Network. The initial results have been published in [1], the current paper focus on increasing the sample convergence rate, and introducing a new filtering approach based on a moving average spatial filter, to increase accuracy. Field tests have been carried out for two radio environments (urban and suburban) in the Lisbon area, Portugal. The new enhancements produced a geopositioning success rate of 47% and 31%, and a median accuracy of 151 m and 337 m, for the urban and suburban environments, respectively. The implemented filter produced a 16% and 20% increase on accuracy, when compared with the geopositioned raw data. The obtained results are rather promising in accuracy and geolocation success rate. OTD positioning smoothed by moving average spatial filtering reveals a strong approach for positioning trace extracted events, vital for boosting Self-Organizing Networks (SON) over a 3G network.

A Model to Evaluate Vertical Handovers on JRRM

In a heterogeneous cellular networks environment, users behaviour and network deployment configuration parameters have an impact on the overall Quality of Service. This paper proposes a new and simple model that, on the one hand, explores the users behaviour impact on the network by having mobility, multi-service usage and traffic generation profiles as inputs, and on the other, enables the network setup configuration evaluation impact on the Joint Radio Resource Management (JRRM), assessing some basic JRRM performance indicators, like Vertical Handover (VHO) probabilities, average bit rates, and number of active users, among others. VHO plays an important role in fulfilling seamless users sessions transfer when mobile terminals cross different Radio Access Technologies (RATs) boundaries. Results show that high bit rate RATs suffer and generate more influence from/on other RATs, by producing additional signalling traffic to a JRRM entity. Results also show that the VHOs probability can range from 5 up to 65%, depending on RATs cluster radius and users mobility profile.

Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization

Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.