Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation
Chapter, Peer reviewed
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Original versionJiao, L., Li, F. Y., & Pla, V. (2011). Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation. In V. Casares-Giner, P. Manzoni & A. Pont (Eds.), Networking 2011 Workshops (Vol. 6827, pp. 22-31): Springer Berlin / Heidelberg.
In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models.
Publishes version of a paper from the book: Networking 2011 Workshops. Also available f rom the publisher on SpringLink:http://dx.doi.org/10.1007/978-3-642-23041-7_3