Marc Majoral

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—In this paper we propose two Reinforcement Learning (RL) algorithms as a solution for the aggregated interference management, in realistic femto networks characterized by high dynamism due to, e.g., mobility of users, lognormal shadowing, fast fading, random activity patterns of femto nodes, etc. We discuss the Q-Learning (QL) algorithm, presented in(More)
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