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Extended Knowledge-Based Reasoning Approach to Spectrum Sensing for Cognitive Radio
April 2010 (vol. 9 no. 4)
pp. 465-478
Xiao Yu Wang, University of Waterloo, Waterloo
Alexander Wong, University of Waterloo, Waterloo
Pin-Han Ho, University of Waterloo, Waterloo
In this paper, a novel scheme for Cognitive Radio (CR) spectrum sensing in Medium Access Control (MAC) layer, called as Extended Knowledge-Based Reasoning (EKBR), is proposed. The target of EKBR is to improve the fine sensing efficiency by jointly considering a number of network states and environmental statistics, including fast sensing results, short-term statistical information, channel quality, data transmission rate, and channel contention characteristics. This is for a better estimation on the optimal range of spectrum for fine sensing so as to adaptively reduce the overall channel sensing time. Performance analysis is conducted on the proposed EKBR scheme using a multidimensional absorbing Markov chain to evaluate various performance metrics of interest, such as average sensing delay (or referred to as sensing overhead in the study), average data transmission rate, and percentage of missed spectrum opportunities. Numerical results show that the proposed EKBR scheme achieves better performance than that by the state-or-the-art techniques while yielding less computation complexity and sensing overhead.

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Index Terms:
Cognitive radio, dynamic spectrum access, spectrum sensing.
Citation:
Xiao Yu Wang, Alexander Wong, Pin-Han Ho, "Extended Knowledge-Based Reasoning Approach to Spectrum Sensing for Cognitive Radio," IEEE Transactions on Mobile Computing, vol. 9, no. 4, pp. 465-478, April 2010, doi:10.1109/TMC.2009.148
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