Technical Note: \cal Q-Learning
Machine Learning
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
OFDMA femtocells: a roadmap on interference avoidance
IEEE Communications Magazine
Spectrum allocation in tiered cellular networks
IEEE Transactions on Communications
Access control mechanisms for femtocells
IEEE Communications Magazine
Open vs. closed access femtocells in the uplink
IEEE Transactions on Wireless Communications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Power Allocation Schemes in OFDM-Based Femtocell Networks
Wireless Personal Communications: An International Journal
Power Control Based on Maximum Power Adaptation in Two-Tier Femtocell Networks
Wireless Personal Communications: An International Journal
Wireless Personal Communications: An International Journal
Realistic Long Term Evolution Performance for Massive HeNB Residential Deployments
Wireless Personal Communications: An International Journal
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Femtocells promise to improve the quality of indoor wireless communications substantially. However, a serious interference problem arises with universal frequency reuse. In this paper, an asynchronous dynamic power allocation among femtocells based on Q-learning is proposed to mitigate the interference in the network. Simulation results show that in the high femtocells density deployment, asynchronous decision-making process has better performance than the synchronous one in terms of both performance degradation of the macrocell and average capacity of femtocells. In addition, it is shown that our method has superiority to smart power control algorithm proposed by 3GPP when femtocell occupation ratio is over 53 %.