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Distributed Learning of Equilibria for a Stochastic Game on Interference Channels

Chaitanya, Krishna A and Sharma, Vinod and Mukherji, Utpal (2015) Distributed Learning of Equilibria for a Stochastic Game on Interference Channels. In: 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), JUN 28-JUL 01, 2015, Stockholm,, SWEDEN, pp. 650-654.

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Official URL: http://dx.doi.org/10.1109/SPAWC.2015.7227118

Abstract

We consider a wireless communication system in which N transmitter-receiver pairs want to communicate with each other. Each transmitter transmits data at a certain rate using a power that depends on the channel gain to its receiver. If a receiver can successfully receive the message, it sends an acknowledgement (ACK), else it sends a negative ACK (NACK). Each user aims to maximize its probability of successful transmission. We formulate this problem as a stochastic game and propose a fully distributed learning algorithm to find a correlated equilibrium (CE). We also propose a fully distributed learning algorithm to find a Pareto optimal solution, and we compare the utilities of each user at the CE and the Pareto point and also with some other well known recent algorithms.

Item Type: Conference Proceedings
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Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 08 Oct 2016 05:42
Last Modified: 08 Oct 2016 05:42
URI: http://eprints.iisc.ernet.in/id/eprint/54747

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