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AuthorElsayed M.H.M.
AuthorMohamed A.
Available date2022-04-21T08:58:30Z
Publication Date2015
Publication Name2015 7th International Conference on New Technologies, Mobility and Security - Proceedings of NTMS 2015 Conference and Workshops
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/NTMS.2015.7266488
URIhttp://hdl.handle.net/10576/30128
AbstractFemtocell networks have become a promising solution in supporting high data rates for 5G systems, where cell densification is performed using the small femtocells. However, femtocell networks have many challenges. One of the major challenges of femtocell networks is the interference management problem, where deployment of femtocells in the range of macro-cells may degrade the performance of the macrocell. In this paper, we develop a new platform for studying interference management in distributed femtocell networks using reinforcement learning approach. We design a complete MAC protocol to perform distributed power allocation using Q-Learning algorithm, where both independent and cooperative learning approaches are applied across network nodes. The objective of the Q-Learning algorithms is to maximize aggregate femtocells capacity, while maintaining the QoS for the Macrocell users. Furthermore, we present the realization of the algorithms using GNURadio and USRP platforms. Performance evaluation are conducted in terms of macrocell capacity convergence to a target capacity and improvement of aggregate femtocells capacity. 2015 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectAggregates
Estimation
Femtocell
Medium access control
Mobile telecommunication systems
Reinforcement learning
Signal to noise ratio
Wave interference
Cognitive femtocell networks
Cooperative learning approach
Distributed interference managements
Distributed Power-Allocation
Femtocell Networks
Media access protocols
Reinforcement learning approach
Resource management
Learning algorithms
TitleDistributed interference management using Q-Learning in cognitive femtocell networks: New USRP-based implementation
TypeConference Paper
dc.accessType Abstract Only


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