Abstract
We consider a wireless communication system in which N transmitter-receiver pairs want to communicate with each other. Each transmitter transmits data 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); and we use a no regret algorithm to find a coarse correlated equilibrium (CCE). We compare the sum rate obtained at the CE, CCE, and a Pareto point, and also via some other well known recent algorithms.
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Chaitanya, A.K., Mukherji, U., Sharma, V. (2017). Learning Equilibria of a Stochastic Game on Gaussian Interference Channels with Incomplete Information. In: Lasaulce, S., Jimenez, T., Solan, E. (eds) Network Games, Control, and Optimization. NETGCOOP 2016. Static & Dynamic Game Theory: Foundations & Applications. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-51034-7_15
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DOI: https://doi.org/10.1007/978-3-319-51034-7_15
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