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Firooznia A.,Technical University of Delft | Bourdais R.,CentraleSupelec IETR | De Schutter B.,Technical University of Delft
Proceedings of the IEEE Conference on Decision and Control | Year: 2016

In this work, a class of model predictive control problems with mixed real-valued and binary control signals is considered. The optimization problem to be solved is a constrained Mixed Integer Quadratic Programming (MIQP) problem. The main objective is to derive a distributed algorithm for limiting the search space in branch and bound approaches by tightening the lower and upper bounds of objective function. To this aim, a distributed algorithm is proposed for the convex relaxation of the MIQP problem via dual decomposition. The effectiveness of the approach is illustrated with a case study. © 2015 IEEE. Source


Modi N.,CentraleSupelec IETR | Mary P.,INSA Rennes | Moy C.,CentraleSupelec IETR
2015 IEEE Globecom Workshops, GC Wkshps 2015 - Proceedings | Year: 2015

In this paper, we propose a novel machine learning algorithm called quality of service upper confidence bound (QoS-UCB) for the opportunistic spectrum access (OSA) scenario. The proposed algorithm selects an optimal channel in terms of occupancy and quality, e.g. signal to noise ratio (SNR) for transmission. It allows secondary users (SU) to learn the spectrum not only on the vacancy point of view but also on the expected transmission quality by selecting two distinguishable exploration coefficients. Our contribution is threefold: i) We propose a new learning algorithm achieving optimal trade-off between exploration and exploitation when OSA scenario is modeled as a Markov multi-armed bandit (MAB) problem. ii) We state that under mild conditions on the state transition probabilities of Markov chains, the regret of the QoS-UCB policy behaves logarithmically over time. iii) We numerically compare our scheme with an existing UCB1 in OSA context and also show that QoS-UCB outperforms traditional UCB1 in terms of regret. © 2015 IEEE. Source


Moy C.,CentraleSupelec IETR | Palicot J.,CentraleSupelec IETR
IEEE Communications Magazine | Year: 2015

In this article, we deal with software radio in an original manner, emphasizing the fact that software radio is a major evolution of radio technologies and a convergence of different pre-existing fields. Joseph Mitola deserves credit for formalizing and conceptualizing this evolution. We do not define software radio. Rather, we look at software radio from different perspectives. New equipments include more and more software radio "capacities," that is, they can be reconfigured thanks to software. Certain former analog functionalities are now performed digitally. We think that the timeframe during which software radio is advantageous, compared to a velcro1 approach for multi-standard terminals, is probably over. However, software radio has taken concrete form in the military field. We show that software radio is used de facto in all equipment and products because of the technological progress to which it has led. Software radio's legacy indeed is that it has been and still is a catalyst for wireless innovation. We conclude by showing that software radio will be used to its full potential when it is the support technology for other more complex fields such as cognitive radio. © 2015 IEEE. Source


Gouldieff V.,CentraleSupelec IETR | Berberidis K.,University of Patras | Palicot J.,CentraleSupelec IETR
2015 23rd European Signal Processing Conference, EUSIPCO 2015 | Year: 2015

In this paper, a method for discrete sources extraction from underdetermined, finite-bandwidth and delayed mixtures of BPSK sources with a single antenna receiver is proposed. Unlike most of the already existing algorithms which consider the unavoidable delay between the sources as undesirable, the proposed method takes advantage of such a delay. Indeed, it turns out that it is possible to recover the symbols even if there is neither gain nor phase diversity. The complexity of the proposed algorithm is quite low, which makes it efficient for real-time sources separation. The effectiveness of the method is illustrated via numerical simulations for different scenarios. © 2015 EURASIP. Source


Penet M.,CentraleSupelec IETR | Gueguen H.,CentraleSupelec IETR | Belmiloudi A.,INSA Rennes
International Journal of Control, Automation and Systems | Year: 2016

This paper presents a robust nonlinear model predictive control strategy to consider the control of systems described by nonlinear ordinary differential equation in a sampled-data framework. The optimal couple controldisturbances is calculated as a time continuous function at each sampling instant by solving a saddle point problem. Using this controller, it is proved that the system is ultimately bounded and satisfies an exponential stability property at each sampling instants. To validate the efficiency of our approach, the presented methodology is illustrated on a cart, spring and damper example. © 2016, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg. Source

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