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Adaptive Learning and Game Theory Based Cognitive Radio Networks |
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PP: 1015-1020 |
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doi:10.18576/amis/130615
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Author(s) |
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P. Arivazhagi,
P. Karthigaikumar,
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Abstract |
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| In this paper, we propose the optimized adaptive spectrum sensing method employing Game Theory Model for Cognitive Radio Networks. In the game theory model, the secondary user (SU) decide the sensing technique applicable relative to the utility function. Prior to this, SU estimates the SNR (Signal-to-Noise Ratio) of each channel and thus forms the utility function in terms instead of energy and throughput. Then the sensing method is adaptively determined on the basis of the SNR value. At low SNR values, the one-order cyclostationary detection technique is applied whereas at high SNR values, the energy detector is used. The decision thresholds λ1 and λ2 of the energy detector and the one-order cyclostationary detector, respectively, are adjusted to maximize the utility. Depending on the results of simulation, it is evident that the proposed technique increases both the energy efficiency and the recognition accuracy.
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