Dayan Adionel Guimarães

Implementation-Oriented Model for Centralized Data-Fusion Cooperative Spectrum Sensing

We propose a new model for a cognitive radio in the scenario of centralized data-fusion cooperative spectrum sensing. The model is grounded on a direct-conversion receiver architecture and was applied to four detection methods: the eigenvalue-based generalized likelihood ratio test, the maximum-minimum eigenvalue detection, the maximum eigenvalue detection and the energy detection. It is shown that the sensing performance under the conventional model typically adopted in the above scenario is overestimated when compared with the proposed one, which suggests that our model better suits for the spectrum sensing design and its performance assessment.

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.

Resource-Efficient Fusion over Fading and Non-Fading Reporting Channels for Cooperative Spectrum Sensing

Recently, a novel resource-efficient technique for the reporting channel transmissions in cooperative spectrum sensing was proposed. In this technique, secondary users are allowed to simultaneously send their local decisions to the fusion center, saving time and frequency resources. Expressions for the probabilities of detection and false alarm for the unitary-gain AWGN reporting channels were derived, while simulation results were given for both the AWGN and Rayleigh fading channels. Here, we provide an expression that is applicable to AWGN channels with different real-valued gains and to time-varying real-valued gains. A simple suboptimum receiver is proposed for the general complex-valued fading and non-fading channels, with an improved performance in the low signal-to-noise ratio condition. Numerical results are shown for both the AWGN and Rayleigh fading reporting channels, demonstrating the accuracy of the derived expressions and the attractive performance of the proposed receiver.

MI-SBTVD: a proposal for the Brazilian digital television system SBTVD

The objective of this paper is to present a general overview of the Innovative Modulation System Project — MI-SBTVD — developed for the Brazilian Digital TV System. The MI-SBTVD Project includes an LDPC high performance error correcting code, an advanced transmit spatial diversity and an efficient multi-carrier modulation scheme. The building blocks of the system, its characteristics and most relevant innovations are presented. The performance of the whole system under different channels is compared with the performance of the present-day Digital Television standards. The complete system was implemented in FPGA using VHDL language and rapid prototyping tools for DSP algorithms.

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.

A Tutorial on the CVX System for Modeling and Solving Convex Optimization Problems

In many areas of knowledge, situations in which we have to model and solve optimization problems are recurrent. Among the mathematical theories that support the solution of such problems, convex optimization unveiled to be an important tool. This is mainly due to the existence of algorithms whose computational solution has matured a lot in terms of speed of solution and reliability during the past few years. In this context, it deserves attention the CVX, a system for modeling and solving convex optimization problems. CVX uses the disciplined convex programming concept, which is a set of conventions or rules that permits the verification of convexity and automatic conversion of the problem instance into forms directly handled by the embedded solvers. This tutorial presents CVX in a didactic manner whose objective is to facilitate the learning about using the tool along with disciplined convex programming. Besides a number of examples, the tutorial also provides some applications, their corresponding CVX codes, the numerical solutions and discussions.

Resource-Efficient Fusion with Pre-Compensated Transmissions for Cooperative Spectrum Sensing

Recently, a novel fusion scheme for cooperative spectrum sensing was proposed for saving resources in the control channel. Secondary users (SUs) simultaneously report their decisions using binary modulations with the same carrier frequencies. The transmitted symbols add incoherently at the fusion centre (FC), leading to a larger set of symbols in which a subset is associated with the presence of the primary user (PU) signal, and another subset is associated with the absence of such a signal. The decision criterion applied for discriminating these subsets works under the assumption that the channel gains are known at the FC. In this paper, we propose a new simultaneous transmission and decision scheme in which the task of channel estimation is shifted from the FC to the SUs, without the need for feeding-back of the estimates to the FC. The estimates are used at the SUs to pre-compensate for the reporting channel phase rotations and to partially compensate for the channel gains. This partial compensation is the result of signal clipping for peak-to-average power ratio (PAPR) control. We show, analytically and with simulations, that this new scheme can produce large performance improvements, yet reduces the implementation complexity when compared with the original one.

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.

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.

Comparison between eigenvalue fusion and decision fusion for spectrum sensing of OFDMA signals under errors in the control channel

Recently, an eigenvalue fusion approach for detecting idle subchannels of OFDMA signals in the context of centralized cooperative spectrum sensing for cognitive radio (CR) was proposed. Four detection techniques were analyzed, and it was concluded that the eigenvalue fusion outperforms the decision fusion scheme, in spite of the larger volume of data sent to the fusion center (FC) in the eigenvalue fusion. Nevertheless, it was conjectured that bit errors in the reporting channel could be more disastrous to the data representing CR decisions than to the data carrying eigenvalues, masking a potential advantage of the eigenvalue combining also in terms of the volume of data sent to the FC. In this paper we investigate this conjecture and conclude that it is partially true: CR decisions are indeed more sensitive to channel errors, but the amount of redundancy inserted to protect the decisions so as to equate the performances of the two fusion schemes does not always leads to a larger number of bits in the decision fusion. Then, one needs to trade performance and amount of data in the reporting channel to decide upon which fusion scheme must be adopted, in a case by case analysis.