Research Article
A context-aware and Intelligent Dynamic Channel Selection scheme for cognitive radio networks
@INPROCEEDINGS{10.1109/CROWNCOM.2009.5189427, author={Kok-Lim Alvin Yau and Peter Komisarczuk and Paul D. Teal}, title={A context-aware and Intelligent Dynamic Channel Selection scheme for cognitive radio networks}, proceedings={4th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications}, publisher={IEEE}, proceedings_a={CROWNCOM}, year={2009}, month={8}, keywords={Cognitive radio networks; dynamic channel selection; context-awareness; intelligence; reinforcement learning}, doi={10.1109/CROWNCOM.2009.5189427} }- Kok-Lim Alvin Yau
Peter Komisarczuk
Paul D. Teal
Year: 2009
A context-aware and Intelligent Dynamic Channel Selection scheme for cognitive radio networks
CROWNCOM
IEEE
DOI: 10.1109/CROWNCOM.2009.5189427
Abstract
The tremendous growth in ubiquitous low-cost wireless applications that utilize the unlicensed spectrum bands has laid increasing stress on the limited and scarce radio spectrum resources. Given that the licensed or Primary Users (PUs) are oblivious to the presence of unlicensed or Secondary Users (SUs), Cognitive Radio (CR) is a new paradigm in wireless communication that allows the SUs to detect and use the underutilized licensed spectrums opportunistically and temporarily. In this paper, we propose a Context-aware and Intelligent Dynamic Channel Selection scheme that helps SUs to select channel adaptively for data transmission to enhance QoS, particularly throughput and delay. Our scheme is suitable for CR networks with mobile hosts. We formulate and design our scheme using Reinforcement Learning that offers a simple and yet practical solution. Channel heterogeneity, which is a feature unique to CR networks that has been ignored in previous studies, is considered in this paper. Simulation results reveal that the proposed scheme achieves very good performance.
