G.T.F. de Abreu

University of Oulu, Oulu, Oulu, Finland

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Publications (79)32.59 Total impact

  • Omotayo Oshiga, Stefano Severi, Giuseppe Abreu
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    ABSTRACT: We consider the problem of performing ranging measurements between a source and multiple receivers efficiently and accurately, as required by distance-based wireless localization systems. To this end, a new multipoint ranging algorithm is proposed, which is obtained by adapting superresolution techniques to the ranging problem, using for the sake of illustration the specific cases of ToA and PDoA, unified under the same mathematical framework. The algorithm handles multipoint ranging in an efficient manner by employing an orthogonalized non-uniform sampling scheme optimised via Golomb rulers. Since the approach requires the design of mutually orthogonal sets of Golomb rulers with equivalent properties -- a problem that founds no solution in current literature -- a new genetic algorithm to accomplish this task is presented, which is also found to outperform the best known alternative when used to generate a single ruler. Finally, a CRLB analysis of the overall optimised multipoint ranging solution is performed, which together with a comparison against simulation results validates the proposed techniques.
    08/2014;
  • Satyanaranaya Vuppala, Giuseppe Abreu
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    ABSTRACT: We investigated the secrecy outage of unicast channels in random networks exposed to unknown numbers of randomly located eavesdroppers, obtaining original expressions which include uncertainty in terms of the location of legitimate nodes relative to eavesdroppers, the number of eavesdroppers, and fading. Under such conditions, we derive the path gain distributions of legitimate and eavesdropper nodes, as well as the corresponding secrecy non-outage. Two interesting conclusions can be drawn from our analysis. The first is that the uncertainty on the number of eavesdropper does not play a significant role in quantifying secrecy outage; and the second is that secret communication at a given rate is possible (albeit subjected to outage), with very low power. Specifically, it is found that the for a given fading figure and network density (which fundamentally determines the secrecy outage) similar secrecy outage is experience by the k-th furthest legitimate node, independent on the source's transmit power.
    Personal Indoor and Mobile Radio Communications (PIMRC), 2013 IEEE 24th International Symposium on; 01/2013
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    ABSTRACT: We propose a new Nakagami phase-envelope fading channel simulator that (i) allows for arbitrary real values of fading parameter, (ii) exactly matches the Nakagami first-order statistics, (iii) and closely matches the second-order statistics classically assigned to Nakagami fading. The proposed simulator is based on a cascade of two existing simulators-the random-mixture simulator and the rank-matching simulator. It combines the strengths of these two simulators, outperforming them both.
    IEEE Transactions on Wireless Communications 01/2013; 12(5):2323-2333. · 2.42 Impact Factor
  • S. Vuppala, G.T.F. de Abreu
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    ABSTRACT: We consider the secrecy capacity of unicast channels of ad hoc networks exposed to randomly located eavesdroppers, as modeled by S-Graphs. Expressions that quantify the impact of fading and of the density of legitimate nodes relative to that of eavesdroppers are obtained, in terms of the probability that secrecy capacities of unicast channels are nonzero. The results indicate that depending on the relative density of eavesdroppers and the fading intensity, the secrecy capacity of unicast channels subject to fading may be higher than under additive white Gaussian noise (AWGN).
    IEEE Transactions on Information Forensics and Security 01/2013; 8(9):1469-1481. · 1.90 Impact Factor
  • D. Macagnano, G.T.F. de Abreu
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    ABSTRACT: We offer a redesigned form of the classical multidimensional scaling (C-MDS) algorithm suitable to handle the localization of multiple sources under line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. To do so we propose to modify the kernel matrix used in the MDS algorithm to allow for both distance and angle information to be processed algebraically (without iteration) and simultaneously. In so doing we also show that the new formulation overcomes two well known limitations of the C-MDS approach, namely the propagation error problem and the possibility to weight the dissimilarities used as measurement information, including, for the case of binary weights, the data erasure problem. Due to the increased size of the proposed edge kernel matrix KE used in the algorithm, the Nystrom approximation is applied to reduce the overall computational complexity to few matrix multiplications. Range only scenarios are also dealt with by approximating the matrix KE. Simulations in range-angle as well as range-only scenarios demonstrate the superiority of our solution under both LOS and NLOS conditions versus semidefinite programming (SDP) formulations of the problem specifically designed to exploit the heterogeneity of the information available.
    IEEE Transactions on Wireless Communications 01/2013; 12(10):5334-5345. · 2.42 Impact Factor
  • S. Vuppala, G. Abreu
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    ABSTRACT: We analyze the effect of fading onto the probability of non-zero secrecy capacity, denoted Pr{Cs:i > 0}, in stochastic wireless random networks modeled as Secrecy-Graphs. Specifically, we derive expressions to characterize the probability that the secrecy capacity of a unicast channel to a legitimate node is non-zero, in the case when the channel is affected by Nakagami-m fading, and in the presence of a random (unknown) number of eavesdroppers. The results show that fading can increase the probability of finding information-theoretic secure channels in such conditions, depending on the relative density of legitimate nodes and eavesdroppers.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
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    ABSTRACT: In this paper we introduce the concept of algebraic confidence, defined as the measure of belief provided by an algebraic algorithm without a priori information of ranging statistics. This is obtained by employing the Circular-based Interval SMACOF (CIS) algorithm which outputs an algebraic confidence level on targets' estimates, without relying on the propagation of location distributions. We illustrate the validity of our confidence by comparing it to the Fisher error ellipses derived from the Cramér-Rao lower bound (CRLB), corroborating the concept. To exploit the proposed confidence measures during the optimization process, we modify the cost function used in the Circular-based Interval SMACOF (CIS) algorithm and describe how to solve the corresponding optimization problem by means of majorization techniques. The resulting CIS+ algorithm is shown to outperform the CIS algorithm both in terms of accuracy as well as in terms of computational complexity.
    Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on; 11/2012
  • Source
    Giuseppe Abreu
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    ABSTRACT: Start of the above-titled section of the conference proceedings record.
    Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on; 01/2012
  • IEEE Transactions on Communications. 01/2012; 60:164-175.
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    ABSTRACT: We address the Primary User (PU) detection (spectrum sensing) problem, relevant to cognitive radio, from a finite random matrix theoretical (RMT) perspective. Specifically, we employ recently-derived closed-form and exact expressions for the distribution of the standard condition number (SCN) of uncorrelated and semi-correlated random dual central Wishart matrices of finite sizes in the design Hypothesis-Testing algorithms to detect the presence of PU signals. In particular, two algorithms are designed, with basis on the SCN distribution in the absence (mathcal{H}_0) and in the presence (mathcal{H}_1) of PU signals, respectively. Due to an inherent property of the SCN's, the mathcal{H}_0 test requires no estimation of SNR or any other information on the PU signal, while the mathcal{H}_1 test requires SNR only. Further attractive advantages of the new techniques are: a) due to the accuracy of the finite SCN distributions, superior performance is achieved under a finite number of samples, compared to asymptotic RMT-based alternatives; b) since expressions to model the SCN statistics both in the absence and presence of PU signal are used, the statistics of the spectrum sensing problem in question is completely characterized; and c) as a consequence of a) and b), accurate and simple analytical expressions for the receiver operating characteristic (ROC) — both in terms of the probability of detection as a function of the probability of false alarm (P_D versus P_F) and in terms of the probability of acquisition as a function of the probability of miss detection (P_A versus P_M) — are yielded. It is also shown that the proposed finite RMT-based algorithms outperform all similar alternatives currently known in the literature, at a substantially lower complexity. In the process, several new results on the distributions of eigenvalues and SCNs of random Wishart Matrices are offered, including a closed-form of the Marchenko-Pastur's Cumulative Density Fun- - ction (CDF) and extensions of the latter, as well as variations of asymptotic the distributions of extreme eigenvalues (Tracy-Widom) and their ratio (Tracy-Widom-Curtiss), which are simpler than those obtained with the "spiked population model".
    IEEE Transactions on Communications 01/2012; · 1.75 Impact Factor
  • Conference Paper: Unicasting on the S-Graph
    S. Vuppala, G. Abreu
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    ABSTRACT: We consider the secrecy capacity of unicast channels of ad hoc networks exposed to randomly located eavesdroppers, as modeled by S-Graphs. Expressions that quantify the impact of fading and of the density of legitimate nodes relative to that of eavesdroppers are obtained, in terms of the probability that secrecy capacities of unicast channels are non-zero. The results indicate that depending on the relative density of eavesdroppers and the fading intensity, the secrecy capacity of unicast channels subject to fading may be higher that under AWGN.
    Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on; 01/2012
  • Golaleh Rahmatollahi, Giuseppe Abreu
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    ABSTRACT: We contribute a new solution to the problem of establishing an analytical relationship between hop-counts under a certain routing policy and Euclidean distances in random networks, both in the linear and planar cases. The contributed solution is unified, in that hop-count distributions have similar expressions both in the 1D and the 2D cases; general in terms of routing policies, in that the effect of any given policy is accounted for by means of a single parameter; closed-form, such that hop-count probability mass functions (PMF's) are given in terms of scaled versions of the closed-form PMF's of the number of nodes; and mathematically tractable, since the derived hop-count distributions are in the form of a difference of the well-known Nakagami-m cumulative density functions (CDF's). Direct and Kullback-Leibler divergence comparisons against empirical data demonstrate the high accuracy of our solution. The simplicity, accuracy and generality of the result owes partly to a self-imposed confinement to connected networks, defined formally in stochastic-geometric terms, which allows for the elimination of recursions and multivariate marginalization commonly required by existing solutions. The contributed results find application in the design and analysis of ad hoc networks, cooperative localization algorithms or latency and energy consumption analysis.
    IEEE Transactions on Communications 01/2012; 60(2):429-444. · 1.75 Impact Factor
  • Davide Macagnano, Giuseppe Thadeu Freitas de Abreu
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    ABSTRACT: In this correspondence, we use a generalization of the Bayesian approach to the multitarget problem that goes under the name of cardinalized probability hypothesis density (CPHD) filter to jointly estimate a time varying number of targets and their locations from sets of noisy range measurements. While in the case of Gaussian linear models a closed-form solution for the CPHD recursion exists in the form of a Gaussian mixture (GM), the more general case of nonlinear systems suboptimal solutions becomes necessary. Due to the Gaussianity assumption in the the GM-CPHD filter, we propose to integrate the square-root cubature Kalman filter (S-CKF) into the GM-CPHD recursion. A novel weighted gating strategy, which exploits the GM implementation of the proposed S-CKF-GM-CPHD filter, is offered to lower the computational time by adaptively increasing the gate sizes in proportion to the likelihood of the single GM components. The results reveal that the proposed gating yields considerable savings in processing requirements compared to no gating, without any significant degradation in performance. In addition, although the run time improvement achieved with elliptical or adaptive gating is equivalent, the latter does not degrade the results.
    IEEE Transactions on Signal Processing 01/2012; 60(3):1533-1538. · 2.81 Impact Factor
  • Source
    Giuseppe Destino, Giuseppe Abreu
    08/2011; , ISBN: 978-953-307-324-8
  • Source
    G.T.F. de Abreu, Wensheng Zhang, Y. Sanada
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    ABSTRACT: We address the Primary User (PU) detection (spectrum sensing) problem, relevant to cognitive radio, from a finite random matrix theoretical (RMT) perspective. Specifically, we employ recently-derived closed-form and exact expressions for the distribution of the standard condition number (SCN) of uncorrelated and semi-correlated random dual Wishart matrices of finite sizes, to design Hypothesis-Testing algorithms to detect the presence of PU signals. An inherent characteristic of the SCN/RMT-based approach, is that no signal-to-noise ratio (SNR) estimation or any other information on the PU signal is required. On top of this property, other attractive advantages of the new techniques are: a) due to the accuracy of the finite SCN distributions, superior performance is achieved under a finite number of samples, compared to asymptotic RMT-based alternatives; b) since expressions to model the SCN statistics both in the absence (H<sub>0</sub>) and presence (H<sub>1</sub>) of PU signal are used, the statistics of the spectrum sensing problem in question is completely characterized; c) as a consequence of a) and b), accurate and simple analytical expressions for the receiver operating characteristic (ROC) - both in terms of P<sub>D</sub> as a function of P<sub>F</sub> and in terms of P<sub>A</sub> as a function of P<sub>M</sub> - are yielded. It is also shown that the proposed finite RMT-based algorithms outperforms all similar alternatives currently known in the literature, at a substantially lower complexity.
    Communications (ICC), 2011 IEEE International Conference on; 07/2011
  • D. Macagnano, G.T.F. de Abreu
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    ABSTRACT: We offer a redesigned form of the multidimensional scaling (MDS) algorithm suitable to the simultaneous tracking of a large number of targets with no a priori mobility models. First, we employ an extreme-value and asymptotic take on the theory of Gershgorin spectrum bounds to perform a detailed statistical analysis of the spectrum of random N × N Gramian matrices which arise from dynamic constructions of MDS kernels where the diagonalizer of a previous kernel is used to construct the next one. The analysis reveals that even if the subspace distance between consecutive kernels is relatively large, the dominant eigenspace of dynamic MDS kernels are, with a high probability quantified analytically, associated with its first rows. This feature is exploited further to design a statistically optimized and truncated variation of the Jacobi algorithm, which converges to the dominant eigenspace of a dynamic MDS kernel as fast as the overall optimal Jacobian, but without the exhaustive search for the elements to be annihilated at each rotation as required in the latter. Under the fact that the Euclidean double-centered kernels of the classic MDS method are asymptotically Gramian, and the knowledge of Nyström-inspired methods to compensate for data erasures, the technique presented yields a very efficient (fast) MDS-based multitarget tracking algorithm which achieves a remarkably low complexity of order O(√(N)), and which is robust to arbitrary statistics of the target's dynamics.
    IEEE Transactions on Signal Processing 05/2011; · 2.81 Impact Factor
  • Davide Macagnano, Giuseppe Abreu
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    ABSTRACT: We consider the simultaneous localization of multiple sources under non-line of sight (NLoS) conditions. The contribution here is an extension of the super multidimensional scaling (MDS) technique, to allow for both distance and angle information to be processed algebraically (without iteration) and simultaneously. Due to the flexibility of the method, the algorithm can be executed relying on the Nyström approximation, reducing computational complexity to that of a few matrix multiplications. Simulations demonstrate the superiority of the proposed solution compared to the standard C-MDS and the SMACOF algorithms.
    Circuits, Systems and Computers, 1977. Conference Record. 1977 11th Asilomar Conference on 01/2011;
  • G.P. Villardi, H. Harada, G.T.F. de Abreu
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    ABSTRACT: We address the problem of interference between cognitive wireless networks coexisting in the TV White Space (TVWS). We perform stochastic geometry analysis in order to evaluate the service area secondary cognitive devices can expect under mild to severe interference of neighboring networks. From our analysis, we foresee severe service area reduction, especially in densely populated areas, indicating a future need for coexistence techniques tailored to enable communication in TVWS while preventing harmful interference between cognitive wireless networks. Furthermore, we give a concise overview of the current activities undergoing in international standardization bodies towards the realization of communications in the TVWS.
    Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2011 Sixth International ICST Conference on; 01/2011
  • Davide Macagnano, Giuseppe Destino, Giuseppe Thadeu Freitas de Abreu
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    ABSTRACT: Solving the distance-based network localization problem typically entails the formulation of an equivalent op- timization problem which is either convex but sub-optimal, or optimal (i.e., maximum-likelihood) but non-convex. We show that the non-convexity implied by the choice of an optimal formulation need not be translated onto high computational complexity nor to performance degradation. To this end, we focus on an approach whereby low-complexity optimization algorithms are coupled with an efficient initialization which in turn, is formulated in terms of an Euclidean Distance Matrix (EDM) completion problem under the condition that the network is percolated (as required by Graph-based Completion). The resulting Hybrid Initialization scheme is shown to be sufficient to bring the performance of low-complexity algorithms such as the SMACOF and the NLS close to that of far more sophisticated alternatives such as the SDP. I. INTRODUCTION Localization is emerging as one of the fundamental feature in future wireless networks. However, while some particular application already find suitable technologies and algorithms to provide location-based services, e.g outdoor navigation using GPS systems, in the general case of low cost wireless sensor networks in which the nodes are randomly deployed and interconnected amongst themselves is still an open prob- lem. In particular, in the area of distance-based network local- ization, several algorithms have been proposed to improve the robustness of the estimates versus corrupted distance observations (1)-(3). However, due to the nonlinar and nonconvex nature of the problem rather an optimal formulation need not be trans- lated onto high computational complexity nor to performance degradation. To this end, we focus on an approach whereby low-complexity optimization algorithms are coupled with an efficient initialization which in turn, is formulated in terms of an efficient and fully algebraic Euclidean Distance Matrix completion technique. It is shown that, under the assumption that the network is percolated (as required by Graph-based Completion) the accuracy achieved by standard low-complex solutions are comparable to the one achieved by a semidefite programming (SDP) formulation of the problem. Moreover, under the different cases investigated all the optimization techniques are shown to perform close to the Cramer-Rao Lower bound (CRLB). The reminder of this article is as follows. In Section II basis formulations of the localization problem are briefly reviewed. Specifically, Section II-A explains how to formulate the problem as an embedding problem by means of the classical MDS solution. Section II-B reviews some of the cost functions embedded in optimization-based solution to the localization problems such as nonlinear least square (NLS), scaling by majorizing a complicated function (SMACOF) and a semidefinite pro- gramming (SDP) formulation. The proposed algebraic hybrid initialization scheme is for non-convex optimization-based solution is proposed in Section III, where it is also compared versus other, more sophisticated solutions. The results for the proposed hybrid initialization approach applied to NLS and SMACOF algorithms are shown in Section V where they are compared versus an SDP formulation of the problem and the Cramer-Rao lower bound (CRLB). Final remarks are offered in Section V.
    01/2011;
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    ABSTRACT: We introduce a cooperative algorithm for self and target network localization with privacy. The algorithm differs form other cooperative localization algorithms in which it does not require nodes to disclose their location or even to measure (or share) their mutual distances. This is achieved by a combination of two factors: a) a novel closed-form statistical relationship between the hop- and Euclidean-distances of distributed random Breadth Search First (BSF) paths; and b) novel multihop localization algorithms. The results, compared against conventional multihop distance collection indicate that, remarkably, the privacy offered by the proposed cooperative localization algorithm does not incur any significant sacrifice in accuracy.
    Circuits, Systems and Computers, 1977. Conference Record. 1977 11th Asilomar Conference on 01/2011;