Rausley Adriano Amaral de Souza

On the multivariate α-µ distribution with arbitrary correlation

In this paper, an exact new closed formula for the multivariate alpha-mu joint probability density function (PDF) is derived allowing for an arbitrary correlation matrix. In addition, the bit error rate (BER) and the outage probability for the selection combining (SC) technique in a correlated alpha-mu fading channel is obtained.

Performance of Cooperative Eigenvalue Spectrum Sensing with a Realistic Receiver Model under Impulsive Noise

In this paper we present a unified comparison of the performance of four detection techniques for centralized data-fusion cooperative spectrum sensing in cognitive radio networks under impulsive noise, namely, the eigenvalue-based generalized likelihood ratio test (GLRT), the maximum-minimum eigenvalue detection (MMED), the maximum eigenvalue detection (MED), and the energy detection (ED). We consider two system models: an implementation-oriented model that includes the most relevant signal processing tasks realized by a real cognitive radio receiver, and the theoretical model conventionally adopted in the literature. We show that under the implementation-oriented model, GLRT and MMED are quite robust under impulsive noise, whereas the performance of MED and ED is drastically degraded. We also show that performance under the conventional model can be too pessimistic if impulsive noise is present, whereas it can be too optimistic in the absence of this impairment. We also discuss the fact that impulsive noise is not such a severe problem when we take into account the more realistic implementation-oriented model.

Maximal-Ratio and Equal-Gain Combining in Hoyt (Nakagami-q) Fading

New, exact expressions for the bivariate Hoyt (Nakagami-q) processes in a nonstationary environment are derived. More specifically, the following are obtained: joint probability density function and joint cumulative distribution function. In addition the outage probability for the Maximal- Ratio and Equal-Gain Combining techniques in a correlated Hoyt channel are obtained. The expressions are mathematically tractable and flexible enough to accommodate a myriad of correlation scenarios, useful in the analysis of a more general fading environment. Index Terms—Nakagami-q (Hoyt), Bivariate Distribution, Correlation, Combiner.

Cooperative Spectrum Sensing Using Eigenvalue Fusion for OFDMA and Other Wideband Signals

In this paper, we propose a new approach for the detection of OFDMA and other wideband signals in the context of centralized cooperative spectrum sensing for cognitive radio (CR) applications. The approach is based on the eigenvalues of the received signal covariance matrix whose samples are in the frequency domain. Soft combining of the eigenvalues at the fusion center is the main novelty. This combining strategy is applied to variants of four test statistics for binary hypothesis test, namely: the eigenvalue-based generalized likelihood ratio test (GLRT), the maximum-minimum eigenvalue detection (MMED), the maximum eigenvalue detection (MED) and the energy detection (ED). It is shown that the eigenvalue fusion can outperform schemes based on decision fusion and sample fusion. A tradeoff is also established between complexity and volume of data sent to the fusion center in all combining strategies.

On the Efficient Generation of -- and -- White Samples with Applications

This paper is concerned with a simple and highly efficient random sequence generator for uncorrelated and variates. The algorithm may yield an efficiency of almost 100%, and this high efficiency can be reached for all special cases such as ,   ,   , Nakagami-m, Nakagami-q, Weibull, Hoyt, Rayleigh, Rice, Exponential, and the One-Sided Gaussian. This generator is implemented via the rejection technique and allows for arbitrary fading parameters. The goodness-of-fit is measured using the Kolmogorov-Smirnov and Anderson-Darling tests. The maximum likelihood parameter estimation for the distribution is proposed and verified against true values of the parameters chosen in the generator. We also provide two important applications for the random sequence generator, the first one dealing with the performance assessment of a digital communication system over the and fading channels and the second one dealing with the performance assessment of the spectrum sensing with energy detection over special cases of these channels. Theoretical and simulation results are compared, validating again the accuracy of the generators.

Efficient Acceptance-Rejection Method for Nakagami-m Complex Samples

The aim of this Letter is to propose simple and efficient simulation means for the Nakagami-m complex signal using the acceptance-rejection algorithm. Two methods are envisaged: (i) one for the general case, which includes both fading and phase parameters; and (ii) another for the particular case, which includes only the fading parameter. In both cases, the samples are drawn from easily-implementable hat functions found in closed-form. For the general case, the efficiency is always in excess of 70% reaching 100% depending on the parameters. For the particular case, the efficiency moves rapidly towards 100% for useful values of the parameter.

A Near-100% Efficient Algorithm for Generating alpha-kappa-#181; and alpha-eta-#181; Variates

In this paper, we propose a simple and highly efficient random sequence generator for α-κ-μ and α-η-μ variates. The proposed algorithm may yield an efficiency of almost 100% for α-κ-μ and α-η-μ. This high efficiency can be reached for all special cases such as α-μ, κ-μ, η-μ, Nakagami-m, Nakagami-q, Weibull, Hoyt, Rayleigh, Rice, Exponential, and the One-Sided Gaussian. These generators are implemented via the rejection technique and allow for arbitrary fading parameters. The goodness-of-fit is objectively measured using the the p-value of the Kolmogorov-Smirnov test.

On the Probability of False Alarm of the Power Spectral Density Split Cancellation Method

The cooperative power spectral density split cancellation (CPSC) method was recently proposed for cooperative spectrum sensing, with the novelties of being robust against noise uncertainty and having low computational complexity. The probability of false alarm has been derived in the related paper, but under assumptions that make it inaccurate. In this letter, we derive the correct cumulative distribution functions of the main random variables that form the decision statistic of the CPSC model. We also derive the correlation coefficient between sub-band decisions, necessary information that was neglected in the reference paper, leading to an expression for the final probability of false alarm that is more accurate than the original one. Our theoretical results are validated with simulations.

A New Spatially Correlated Shadowed Channel Model with Cognitive Radio Application

In this paper, a new correlated shadowed channel model based on grid points is proposed. It is presented a three-dimensional model capitalizing on the two-dimensional model available in the literature. Additionally, a closed-formula to obtain the theoretical correlation between any two points is derived. In order to show the usefully of the proposed model and as an application example, we provide an important performance analysis related to spectrum sensing for cognitive radio. The effect of correlation in the various aspects of system performance is then investigated. The validity of the analytical results is supported by means of Monte Carlo simulation. The results show that the system performance analysis is more accurate when the proposed model is considered, this conclusion is discussed throughout the paper.

Snapping shrimp noise reduction using convex optimization for underwater acoustic communication in warm shallow water

We propose an ambient noise reduction technique for underwater acoustic communication systems in warm shallow water, where the snapping shrimp impulsive noise is a common impairment. This noise is emitted at the cavitation bubble collapse caused by the claw shut, and can produce very high acoustic pressures which are responsible for the impulsiveness of the noise. The denoised signal is the solution of an unconstrained scalarized bi-criterion convex optimization problem. One of the criterions is based on the robust least-squares signal reconstruction approach, for which the sum of the Huber penalty function of the residuals is minimized. The other criterion uses a quadratic smoothing regularization term, acting on the first-difference of the denoised signal samples. It is shown that the proposed technique can significantly reduce the ambient noise and, thus, reduce the bit error rate of an underwater digital communication system.