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To achieve high data rates and better connectivity in future communicationnetworks, the deployment of different types of access points (APs) is underway.In order to limit human intervention and reduce costs, the APs are expected tobe equipped with self-organizing capabilities. Moreover, due to the spectrumcrunch, frequency reuse among the deployed APs is inevitable, aggravating theproblem of inter-cell interference (ICI). Therefore, ICI mitigation inself-organizing networks (SONs) is commonly identified as a key radio resourcemanagement mechanism to enhance performance in future communication networks.With the aim of reducing ICI in a SON, this paper proposes a novel solution forthe uncoordinated channel and power allocation problems. Based on themulti-player multi-armed bandit (MAB) framework, the proposed technique doesnot require any communication or coordination between the APs. The case ofvarying channel rewards across APs is considered. In contrast to previous workon channel allocation using the MAB framework, APs are permitted to choosemultiple channels for transmission. Moreover, non-orthogonal multiple access(NOMA) is used to allow multiple APs to access each channel simultaneously.This results in an MAB model with varying channel rewards, multiple plays andnon-zero reward on collision. The proposed algorithm has an expected regret inthe order of O(log^2 T ), which is validated by simulation results. Extensivenumerical results also reveal that the proposed technique significantlyoutperforms the well-known upper confidence bound (UCB) algorithm, by achievingmore than a twofold increase in the energy efficiency.

Resource Allocation in NOMA-based Self-Organizing Networks using Stochastic Multi-Armed Bandits