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Cognitive Radio (CR) is an auspicious solution to current problem of spectrum scarcity due to evaluation of new technologies. These techniques are useful in detecting spectral holes, and allocating them to secondary users. Energy Detection is a predominant method for spectrum sensing due to its low computational complexity and capability of detecting spectrum holes without requiring apriori knowledge...
Cognitive radio (CR) is a software defined radio with artificial intelligence (AI) i.e. it can learn from and adapt to ambient radio environment. Most of the research in the field of CR has been centered around policy-based systems that are hard-coded with certain rules for reasoning and learning capabilities for very specific applications. In CR networks, multiple interacting capabilities are required...
This paper presents a Compressive Spectrum Sensing (CSS) technique for wideband Cognitive Radio (CR) system to shorten spectrum sensing interval. Fast and efficient CSS is used to detect wideband spectrum, where samples are taken at sub-Nyquist rate and signal acquisition is terminated automatically once the samples are sufficient for the best spectral recovery. To improve sensing performance we propose...
Cognitive radio (CR) is a technology that addresses the problem of scarcity of spectrum and paves the way for efficient use of the same. In recent times, it has been observed that most research is focused on building theoretical models which are backed mostly by simulation results. In order to successfully support any theoretically developed model, it is necessary that the algorithm be tested in practical...
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