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We study a distributed user association algorithm for a heterogeneouswireless network with the objective of maximizing the sum of the utilities (onthe received throughput of wireless users). We consider a state dependentwireless network, where the rate achieved by the users are a function of theiruser associations as well as the state of the system. We consider threedifferent scenarios depending on the state evolution and the users$\text{'}$knowledge of the system state. In this context, we present completely uncoupleduser association algorithms for utility maximization where the users$\text{'}$association is entirely a function of its past associations and its receivedthroughput. In particular, the user is oblivious to the association of theother users in the network. Using the theory of perturbed Markov chains, weshow the optimality of our algorithms under appropriate scenarios.

Completely Uncoupled User Association Algorithms for State Dependent Wireless Networks