A power control algorithm based on Dyna-Q learning for ultra-dense networks
Xinyong Jia,
Yi Wang,
Jinquan Wang
et al.
Abstract:With ultra-dense networks, the large number of densely deployed low-power base stations creates more serious interference problems for the network. To address this problem, we introduce Dyna-Q learning into the power control problem of ultra-dense networks and propose a power control algorithm based on Dyna-Q learning. Firstly, we build an experience pool to store the state and selected actions of the agent during the operation; Secondly, the agent observes the current state, uses an action selection strategy … Show more
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