Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Estudo de Superfícies Seletivas de Frequência com o Uso de Inteligência Computacional

The main objective of this work is to optimize the performance of frequency selective surfaces (FSS) composed of crossed dipole conducting patches. The optimization process is performed by determining proper values for the width of the crossed dipoles and for the FSS array periodicity, while the length of the crossed dipoles is kept constant. Particularly, the objective is to determine values that provide wide bandwidth using a search algorithm with representation in bioinspired real numbers. Typically FSS structures composed of patch elements are used for band rejection filtering applications. The FSS structures primarily act like filters depending on the type of element chosen. The region of the electromagnetic spectrum chosen for this study is the one that goes from 7 GHz to 12 GHz, which includes mostly the X-band. This frequency band was chosen to allow the use of two X-band horn antennas, in the FSS measurement setup. The design of the FSS using the developed genetic algorithm allowed increasing the structure bandwidth

Anisotropias da radiação cósmica de fundo e vínculos em modelos com decaimento do vácuo

Many astronomical observations in the last few years are strongly suggesting that the current Universe is spatially flat and dominated by an exotic form of energy. This unknown energy density accelerates the universe expansion and corresponds to around 70% of its total density being usually called Dark Energy or Quintessence. One of the candidates to dark energy is the so-called cosmological constant (Λ) which is usually interpreted as the vacuum energy density. However, in order to remove the discrepancy between the expected and observed values for the vacuum energy density some current models assume that the vacuum energy is continuously decaying due to its possible coupling with the others matter fields existing in the Cosmos. In this dissertation, starting from concepts and basis of General Relativity Theory, we study the Cosmic Microwave Background Radiation with emphasis on the anisotropies or temperature fluctuations which are one of the oldest relic of the observed Universe. The anisotropies are deduced by integrating the Boltzmann equation in order to explain qualitatively the generation and c1assification of the fluctuations. In the following we construct explicitly the angular power spectrum of anisotropies for cosmologies with cosmological constant (ΛCDM) and a decaying vacuum energy density (Λ(t)CDM). Finally, with basis on the quadrupole moment measured by the WMAP experiment, we estimate the decaying rates of the vacuum energy density in matter and in radiation for a smoothly and non-smoothly decaying vacuum