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A Distributed User Association Algorithm for State Dependent Wireless Networks

机译:状态依存无线网络的分布式用户关联算法

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We study a distributed user association algorithm for a heterogeneous wireless network with the objective of maximizing the sum of the utilities (on the received throughput)of wireless users. We consider a state-dependent wireless network where the rate achieved by the users are a function of their user associations as well as the state of the system. Also, we model the network to adapt its state based on the user associations. In this context, we present a completely uncoupled user association algorithm for utility maximization where the user's association is entirely a function of its past associations and its received throughput. In particular, the user is oblivious to the network state (and its evolution) as well as the association of the other users in the network. Using the theory of perturbed Markov chains [1], we show the optimality of our algorithm under appropriate scenarios.
机译:我们研究一种用于异构无线网络的分布式用户关联算法,其目的是最大化无线用户的实用程序总和(在接收的吞吐量上)。我们考虑一个状态相关的无线网络,其中用户获得的速率是他们的用户关联以及系统状态的函数。同样,我们基于用户关联对网络进行建模以适应其状态。在这种情况下,我们提出了一种用于效用最大化的完全不耦合的用户关联算法,其中用户的关联完全取决于其过去的关联及其接收的吞吐量。尤其是,用户将忽略网络状态(及其演进)以及网络中其他用户的关联。使用扰动马尔可夫链[1]的理论,我们证明了在适当情况下算法的最优性。

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