@conference { ISI:000381477900056,
	title = {A Distributed Open-Close Access for Small-Cell Networks: A Random Matrix Game Analysis},
	booktitle = {2015 INTERNATIONAL WIRELESS COMMUNICATIONS \& MOBILE COMPUTING CONFERENCE (IWCMC)},
	series = {International Wireless Communications and Mobile Computing Conference},
	year = {2015},
	note = {11th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC), Dubrovnik, CROATIA, AUG 24-25, 2015},
	pages = {320-325},
	publisher = {IEEE; IEEE Croatia Sect; Univ Dubrovnik},
	organization = {IEEE; IEEE Croatia Sect; Univ Dubrovnik},
	abstract = {Nowadays, Small-Cells are widely being deployed to assist and improve performance of mobile networks. Indeed, they are a promising solution to improve coverage and to offload data traffic in mobile networks. In this paper, we propose a signaling-less architecture of the heterogeneous network composed of one single Macro Base Station and a Single Small-Cell. First, we construct a game theoretic framework for channel-state independent interaction. We present many conditions for the existence of Pure Nash equilibrium. Next, and in order to capture the continuous change of the channel state, we build a random matrix game where the channel state is considered to be random (potentially ruled by some given distribution). A characterization of Nash equilibrium is provided in terms of pure strategies and mixed strategies. Convergence to Nash equilibrium is furthermore guaranteed using a variant of the well-known Combined fully distributed payoff and strategy learning. Our algorithm converges faster (only 10-20 iterations are required to converge to Nash equilibrium) and only need a limited amount of local information. This is quite promising since it says that our scheme is almost applicable for all environments (fast fading included).},
	isbn = {978-1-4799-5344-8},
	issn = {2376-6492},
	author = {Ben Chekroun, Samia and Sabir, Essaid and Kobbane, Abdellatif and Tembine, Hamidou and Bouyakhf, El-Houssine and Ibrahimi, Khalil}
}
@article { ISI:000305225200001,
	title = {Dynamic power control for energy harvesting wireless multimedia sensor networks},
	journal = {EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING},
	year = {2012},
	abstract = {Optimization of energy usage in wireless sensor networks (WSN) has been an active research field for the last decades and various approaches have been explored. In fact, A well designed energy consumption model is the foundation for developing and evaluating a power management scheme in network of energy constrained devices such as: WSN. We are interested in developing optimal centralized power control policies for energy harvesting wireless multimedia sensor networks (WMSN) equipped with photovoltaic cells. We propose a new complete information Markov decision process model to characterize sensor{\textquoteright}s battery discharge/recharge process and inspect the structural properties of optimal transmit policies.},
	issn = {1687-1499},
	doi = {10.1186/1687-1499-2012-158},
	author = {Koulali, Mohammed-Amine and Kobbane, Abdellatif and El Koutbi, Mohammed and Tembine, Hamidou and Ben-Othman, Jalel}
}
@article { ISI:000293491800013,
	title = {Dynamic robust power allocation games under channel uncertainty and time delays},
	journal = {COMPUTER COMMUNICATIONS},
	volume = {34},
	number = {12},
	year = {2011},
	month = {AUG 2},
	pages = {1529-1537},
	abstract = {In this paper, we study dynamic robust power allocation strategies under the imperfectness of the channel state information at the transmitters. Considering unknown payoff functions at the transmitters, we propose an heterogeneous Delayed COmbined fully Distributed Payoff and Strategy Reinforcement Learning (Delayed-CODIPAS-RL) in which each transmitter learns its payoff function as well as its associated optimal strategies in the long-term. We show that equilibrium power allocations can be obtained using the multiplicative weighted imitative CODIPAS-RLs and Bush-Mosteller based CODIPAS-RL. We also show almost sure convergence to the set of global optima for specific scenarios. (C) 2011 Elsevier B.V. All rights reserved.},
	issn = {0140-3664},
	doi = {10.1016/j.comcom.2011.02.009},
	author = {Tembine, Hamidou and Kobbane, Abdellatif and El koutbi, Mohamed}
}
