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