Skip to Main content Skip to Navigation
New interface
Journal articles

Distributed Learning in Noisy-Potential Games for Resource Allocation in D2D Networks

Abstract : We propose a distributed learning algorithm for the resource allocation problem in Device-to-Device (D2D) wireless networks that takes into account the throughput estimation noise. We first formulate a stochastic optimization problem with the objective of maximizing the generalized alpha fair function of the network. In order to solve it distributively, we then define and use the framework of noisy-potential games. In this context, we propose a distributed Binary Log-linear Learning Algorithm (BLLA) that converges to a Nash Equilibrium of the resource allocation game, which is also an optimal resource allocation for the optimization problem. A key enabler for the analysis of the convergence are the proposed rules for computation of resistance of trees of perturbed Markov chains. The convergence of BLLA is proved for bounded and unbounded noise, with fixed and decreasing temperature parameter. A sufficient number of estimation samples is also provided that guarantees the convergence to an optimal state. At last, we assess the performance of BLLA by extensive simulations by considering both bounded and unbounded noise cases and we show that BLLA achieves higher sum data rate compared to the state-of-the-art.
Complete list of metadata

Cited literature [36 references]  Display  Hide  Download
Contributor : Marceau Coupechoux Connect in order to contact the contributor
Submitted on : Friday, December 20, 2019 - 11:29:39 AM
Last modification on : Saturday, October 15, 2022 - 3:33:51 AM
Long-term archiving on: : Saturday, March 21, 2020 - 4:06:00 PM


Files produced by the author(s)



Mohammed Shabbir Ali, Pierre Coucheney, Marceau Coupechoux. Distributed Learning in Noisy-Potential Games for Resource Allocation in D2D Networks. IEEE Transactions on Mobile Computing, 2020, 19 (12), pp.2761-2773. ⟨10.1109/TMC.2019.2936345⟩. ⟨hal-02315135⟩



Record views


Files downloads