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Communication Dans Un Congrès SPAWC '12 : The 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications Année : 2012

Distributed stochastic learning for continuous power control in wireless networks

Résumé

In this paper, we develop a distributed stochastic learning framework for seeking Nash equilibria under state dependent payoff functions. Most of the existing works assumes that a closed form expression of the reward is available at the nodes. We consider here a realistic assumption that the nodes have only a numerical realization of the reward at each time and develop a discrete time stochastic learning using sinus perturbation. We examine the convergence of our discrete time algorithm to a limiting trajectory defined by an Ordinary Differential Equation (ODE). Finally, we conduct a stability analysis and apply the proposed scheme in a generic power control problem in wireless networks.
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Dates et versions

hal-00728790 , version 1 (06-09-2012)

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Citer

Ahmed Farhan Hanif, Hamidou Tembine, Mohamad Assaad, Djamal Zeghlache. Distributed stochastic learning for continuous power control in wireless networks. SPAWC '12 : The 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications, Jun 2012, Çesme, Turkey. pp.199-203, ⟨10.1109/SPAWC.2012.6292887⟩. ⟨hal-00728790⟩
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