Probability Density Function based Adaptive Spectrum Sensing for Throughput Maximization in Cognitive Radio Network
نویسندگان
چکیده
In a cognitive radio network, the spectrum sensing must be done quickly and accurately to avoid primary interference and to achieve high throughput. Sensing a channel for a long reduces the throughput and increases the energy wastage. A probability density function (pdf) based adaptive sensing method is proposed in which either a pdf based spectrum sensing or a detailed cyclostationary approach is adopted according to the Signal to Noise ratio (SNR). Simulated results confirmed that the method proposed attains considerable improvement in the throughput and reduction in mean sensing time. Keywords-Cognitive radio Network, probability density function, spectrum sensing, throughput maximization, mean detection time
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