  The deployment of ultra-dense networks is one of the main methods to meet the
5G data rate requirements. However, high density of independent small base
stations (SBSs) will increase the interference within the network. To
circumvent this interference, there is a need to develop self-organizing
methods to manage the resources of the network. In this paper, we present a
distributed power allocation algorithm based on multi-agent Q-learning in an
interference-limited network. The proposed method leverages coordination
through simple message passing between SBSs to achieve an optimal joint power
allocation. Simulation results show the optimality of the proposed method for a
two-user case.
