A distributed network selection scheme in next generation heterogeneous wireless networks
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
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ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Optimal network selection in heterogeneous wireless multimedia networks
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Traffic-aware optimization of heterogeneous access management
IEEE Transactions on Communications
Computer Networks: The International Journal of Computer and Telecommunications Networking
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NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part II
Computer Networks: The International Journal of Computer and Telecommunications Networking
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International Journal of Communication Systems
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Computer Networks: The International Journal of Computer and Telecommunications Networking
RAT selection for heterogeneous wireless networks using support vector machine
Proceedings of the 2013 Research in Adaptive and Convergent Systems
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This paper addresses the problem of Radio Access Technology (RAT) selection in heterogeneous multi-access/multi-service scenarios. For such purpose, a Markov model is proposed to compare the performance of various RAT selection policies within these scenarios. The novelty of the approach resides in the embedded definition of the aforementioned RAT selection policies within the Markov chain. In addition, the model also considers the constraints imposed by those users with terminals that only support a subset of all the available RATs (i.e. multi-mode terminal capabilities). Furthermore, several performance metrics may be measured to evaluate the behaviour of the proposed RAT selection policies under varying offered traffic conditions. In order to illustrate the validation and suitability of the proposed model, some examples of operative radio access networks are provided, including the GSM/EDGE Radio Access Network (GERAN) and the UMTS Radio Access Network (UTRAN), as well as several service-based, load-balancing and terminal-driven RAT selection strategies. The flexibility exhibited by the presented model enables to extend these RAT selection policies to others responding to diverse criteria. The model is successfully validated by means of comparing the Markov model results with those of system-level simulations.