0000000000210416

AUTHOR

Younes Abdi

showing 5 related works from this author

Linear fusion of interrupted reports in cooperative spectrum sensing for cognitive radio networks

2015

Interrupted reporting has recently been introduced as an effective method to increase the energy efficiency of cooperative spectrum sensing schemes in cognitive radio networks. In this paper, joint optimization of the reporting and fusion phases in a cooperative sensing with interrupted reporting is considered. This optimization aims at finding the best weights used at the fusion center to construct a linear fusion of the received interrupted reports, jointly with Bernoulli distributions governing the statistical behavior of the interruptions. The problem is formulated by using the deflection criterion and as a nonconvex quadratic program which is then solved for a suboptimal solution, in a…

ta113Mathematical optimizationFusionta213Artificial neural networkComputer sciencedecision fusioncooperative spectrum sensingBernoulli's principleCognitive radionon-ideal reporting channelscorrelationcognitive radio (CR)Quadratic programmingEfficient energy use2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
researchProduct

The Max-Product Algorithm Viewed as Linear Data-Fusion: A Distributed Detection Scenario

2019

In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a distributed hypothesis test conducted by a max-product iteration over a binary-valued pairwise Markov random field and show that the decision variables obtained are linear combinations of the local log-likelihood ratios observed in the network. Then, we use these linear combinations to formulate the system performance in terms of the false-alarm and detection probabilities. Our findings indicate that, in the hypothesis test concerned, the optimal performance of the max-product a…

FOS: Computer and information sciencesfactor graphsComputer scienceComputer Science - Information TheoryMarkovin ketjut02 engineering and technologyMarkov random fieldsalgoritmit0202 electrical engineering electronic engineering information engineeringMaximum a posteriori estimationmax-product algorithmElectrical and Electronic EngineeringLinear combinationStatistical hypothesis testingdistributed systemsMarkov random fieldspectrum sensingApplied MathematicsNode (networking)Information Theory (cs.IT)linear data-fusionApproximation algorithm020206 networking & telecommunicationsComputer Science Applicationssum-product algorithmPairwise comparisonRandom variableAlgorithmstatistical inference
researchProduct

Modeling and Mitigating Errors in Belief Propagation for Distributed Detection

2021

We study the behavior of the belief-propagation (BP) algorithm affected by erroneous data exchange in a wireless sensor network (WSN). The WSN conducts a distributed multidimensional hypothesis test over binary random variables. The joint statistical behavior of the sensor observations is modeled by a Markov random field whose parameters are used to build the BP messages exchanged between the sensing nodes. Through linearization of the BP message-update rule, we analyze the behavior of the resulting erroneous decision variables and derive closed-form relationships that describe the impact of stochastic errors on the performance of the BP algorithm. We then develop a decentralized distribute…

hajautetut järjestelmätFOS: Computer and information sciencesfactor graphsComputer scienceComputer Science - Information TheoryBinary number02 engineering and technologycommunication errorsBelief propagationcomputation errorslangaton tiedonsiirtooptimointiLinearizationalgoritmit0202 electrical engineering electronic engineering information engineeringlikelihood-ratio testmessage-passing algorithmsElectrical and Electronic EngineeringStatistical hypothesis testingdistributed systemsMarkov random fieldsignaalinkäsittelyInformation Theory (cs.IT)linear data-fusionsensoriverkot020206 networking & telecommunicationscooperative communicationsData exchange020201 artificial intelligence & image processingblind signal processingRandom variableWireless sensor networkAlgorithm
researchProduct

Random Interruptions in Cooperation for Spectrum Sensing in Cognitive Radio Networks

2015

In this paper, a new cooperation structure for spectrum sensing in cognitive radio networks is proposed which outperforms the existing commonly-used ones in terms of energy efficiency. The efficiency is achieved in the proposed design by introducing random interruptions in the cooperation process between the sensing nodes and the fusion center, along with a compensation process at the fusion center. Regarding the hypothesis testing problem concerned, first, the proposed system behavior is thoroughly analyzed and its associated likelihood-ratio test (LRT) is provided. Next, based on a general linear fusion rule, statistics of the global test summary are derived and the sensing quality is cha…

FOS: Computer and information sciencesSemidefinite programmingMathematical optimizationta213Computer scienceInformation Theory (cs.IT)Computer Science - Information Theory010401 analytical chemistrydecision/data fusion020206 networking & telecommunications02 engineering and technology01 natural sciencesStatistical power0104 chemical sciencescooperative spectrum sensingCognitive radionon-ideal reporting channelsefficiency0202 electrical engineering electronic engineering information engineeringcognitive radio (CR)False alarmElectrical and Electronic EngineeringStatistical hypothesis testingEfficient energy use
researchProduct

Optimization of Linearized Belief Propagation for Distributed Detection

2020

In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP algorithm in a network of distributed agents can be approximated by a linear fusion of all the local log-likelihood ratios. The proposed approach clarifies how the BP algorithm works, simplifies the statistical analysis of its behavior, and enables us to develop a performance optimization framework for the BP-based distributed inference systems. Next, we propose a blind learning-adaptation scheme to optimize the system performance when there is no information available a pr…

hajautetut järjestelmätComputer scienceInference02 engineering and technologyBelief propagation01 natural sciencesMarkov random fieldsalgoritmit0202 electrical engineering electronic engineering information engineering0101 mathematicsElectrical and Electronic Engineeringtilastolliset mallitdistributed systemsbelief-propagation algorithmRandom fieldMarkov chainspectrum sensingverkkoteoriasignaalinkäsittely010102 general mathematicslinear data-fusionApproximation algorithm020206 networking & telecommunicationsCognitive radioblind signal processingAlgorithmWireless sensor networkRandom variablestatistical inference
researchProduct