Fabricio B. S. de Carvalho

Propagation analysis in Precision Agriculture environment using XBee devices

Precision Agriculture (PA) is a method for estimating, assessing and controlling agricultural practices. It emerged from the need for technologies to collect and transmitt data in agricultural areas. On the other hand, the evolution of wireless sensor nodes technology enabled the deployment of Wireless Sensor Networks (WSNs) in agricultural environments. The lack of path loss models for predicting attenuation in vineyard vegetation motivates the study of propagation in this kind of environment. Thus, the objective of this research is to assess signal propagation in a vineyard. In this paper, the impact of different propagation directions was assessed considering the angle between the transmission path and the crop rows (θ). From the experiments, it was possible to find the main attenuation factors of the plantation field and obtain a path loss prediction model that fits well to measurements.

Development of a Smart Building Wireless Sensors Network: Cooperation between University of Washington Tacoma and Brazilian universities

The Institute of Technology at the University of Washington Tacoma - UWT is expanding its international cooperation by hosting Brazilian undergraduate and graduate students in the Computer Engineering and Systems program. In the first research project originated from this cooperation we propose a generic and scalable system, based on Wireless Sensor Networks (WSN). Using the data acquired from the sensor nodes this system will be able to take simple decisions, such as turn on/off heater and lights and help in other more complex decisions, such as rearranging rooms based on the occupancy. These actions aim to save resources and make buildings more comfortable and efficient. In this paper we describe how this research project is being structured and conducted in order to maximize the cooperation between Brazilian and UWT researchers. Also, we show which strategies are being adopted to make the project scalable and generic. This will allow us to aggregate multi-disciplinary people and make the knowledge and technology produced to be reusable by future project members.

A Modified Jarque-Bera Test for Spectrum Sensing in Cognitive Networks Subject to Rayleigh Fading

This paper presents a new algorithm based on the Jarque-Bera (JB) test for spectrum sensing in cognitive networks subject to Rayleigh fading. In the proposed method, based on JB statistical test, fading that affects the spectral detection is considered. The performance of the method is evaluated, using Monte-Carlo simulations, and compared with the Energy Detector (ED) performance. It is shown that the detection probability performance of the proposed method outperforms the original JB test and ED detection when the channel is subject to Rayleigh fading.

Cognitive spectrum sensing via statistical tests in Rice fading channels

Spectrum sensing is an important tool for the expansion of cognitive radio. This paper evaluates the use of statistical tests to optimize the spectral detection of available frequency bands for opportunistic occupation. Statistical characteristics of the transmitted signals over a channel subject to Rice fading are selected to achieve better cognitive sensing performance. More precisely, Jarque-Bera, Kurtosis and Skewness statistical tests are compared via simulation in terms of their detection probabilities in non-fading and in Rice fading channels. Simulation results indicate that these statistical tests are useful, and can be effectively applied to cognitive wireless channels subjected to fading.

Spectrum sensing via statistic tests in Rayleigh fading channels

Cognitive radio applications are limited by the scarcity of available frequency bands for telecommunication services. The improvement of the spectrum sensing to enable a better sharing of the frequency spectrum among different users is a major challenge in wireless communications based on cognitive radio. This paper evaluates the use of statistic tests to optimize the non-cooperative cognitive spectrum sensing. Statistical characteristics of the transmitted signals are selected to achieve better cognitive sensing performance. More precisely, Jarque-Bera, Kurtosis and Skewness statistic tests are compared in Rayleigh fading channel and non-fading scenarios. Simulation results indicate that these statistic tests can be effectively applied to cognitive wireless channels that are subjected to fading.

Cognitive spectrum sensing based on statistical tests in fading channels

The cognitive radio concept is fostered by the scarcity of frequency bands for wireless communication. Several new techniques and algorithms are being proposed to deal with the spectrum occupancy in cognitive channels. The goal is to enable a better sharing of the frequency spectrum among different users. This paper evaluates the performance of statistical tests to optimize the spectrum sensing for fading channels. Statistical characteristics of the transmitted signals can be used to achieve better cognitive sensing performance. Jarque-Bera, Kurtosis and Skewness statistical tests are evaluated when subject to fading effects. Rayleigh, Nakagami-m, Rice and Lognormal fading channels are simulated. Results indicate that these statistical tests can be applied to cognitive wireless channels even when subject to fading.