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License-assisted access LTE (LAA-LTE) has been proposed to deal with theintense contradiction between tremendous mobile traffic demands and crowdedlicensed spectrums. In this paper, we investigate the coexistence mechanism forLAA-LTE based heterogenous networks (HetNets). A joint resource allocation andnetwork access problem is considered to maximize the normalized throughput ofthe unlicensed band while guaranteeing the quality-of-service requirements ofincumbent WiFi users. A two-level learning-based framework is proposed to solvethe problem by decomposing it into two subproblems. In the master level, aQ-learning based method is developed for the LAA-LTE system to determine theproper transmission time. In the slave one, a game-theory based learning methodis adopted by each user to autonomously perform network access. Simulationresults demonstrate the effectiveness of the proposed solution.

A Learning-Based Coexistence Mechanism for LAA-LTE Based HetNets