DocumentCode :
2324434
Title :
A Q-learning based approach to interference avoidance in self-organized femtocell networks
Author :
Bennis, Mehdi ; Niyato, Dusit
Author_Institution :
Centre for Wireless Commun., Univ. of Oulu, Oulu, Finland
fYear :
2010
fDate :
6-10 Dec. 2010
Firstpage :
706
Lastpage :
710
Abstract :
The femtocell concept is an emerging technology for deploying the next generation of the wireless networks, aiming at indoor coverage enhancement, increasing capacity, and offloading the overlay macrocell traffic. Nevertheless, the detrimental factor in such networks is co-channel interference between macrocells and femtocells, as well as among neighboring femtocells. This in turn can dramatically decrease the overall capacity of the network. In addition, due to their non-coordinated nature, femtocells need to self-organize in a distributed manner not to cause interference on the macrocell, while at the same time managing interference among neighboring femtocells. This paper proposes and analyzes a Reinforcement-Learning (RL) framework where a macrocell network is underlaid with femtocells sharing the same spectrum. A distributed Q-learning algorithm is proposed in which each Femto Base Station/Access Point (FBS/FAP) gradually learns (by interacting with its local environment) through trials and errors, and adapt the channel selection strategy until reaching convergence. The proposed Q-learning algorithm is cast into high level and low level subproblems, in which the former finds in a decentralized way the channel allocation through Q-learning, while the latter computes the optimal power allocation. Investigations show that through learning, femtocells are not only able to self-organize with only local information, but also mitigate their interference towards the macrocell network.
Keywords :
cochannel interference; femtocellular radio; indoor communication; interference suppression; learning (artificial intelligence); next generation networks; resource allocation; telecommunication computing; telecommunication traffic; access point; channel allocation; cochannel interference; distributed Q-learning; femto base station; indoor coverage enhancement; interference avoidance; macrocell network; next generation networks; optimal power allocation; overlay macrocell traffic; reinforcement learning; self-organized femtocell networks; wireless networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
GLOBECOM Workshops (GC Wkshps), 2010 IEEE
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-8863-6
Type :
conf
DOI :
10.1109/GLOCOMW.2010.5700414
Filename :
5700414
Link To Document :
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