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In cognitive radio networks, since cognitive terminals use a shared wideband frequency spectrum for data transmissions, they are susceptible to malicious denial‐of‐service attacks, where adversaries try to corrupt communication by actively transmitting interference signals. To address this issue, in this paper, we propose a novel signal separation algorithm based on compressed sensing, which can not...
Spectrum awareness is a prominent characteristic of cognitive radio technologies. Realizing such awareness in cognitive radio requires a capability to recognize the incoming signal's modulation type. In this paper, a novel approach to classify digital modulated signals is proposed for cognitive radio. This method combines high-order spectra with sparse representation. We cast the modulation classification...
In compressed sensing, sparse and compressible signals can be characterized at low sampling rate. In this paper, we focus on locating sub bands frequency adaptively over wideband frequency based on compressed sensing and wavelet edge detection. Based on this, double threshold energy detection of cooperative spectrum sensing is implemented. The analytical results indicate that this novel spectrum sensing...
In this paper, we propose a mathematical framework to maximize the user throughput in a wireless channel using various parameters such the symbol rate, the packet length, and the constellation size as optimization variables. The optimization equations with each of the above degrees of freedom have been presented. We see a gain in choosing the parameters using a theoretical framework. We also present...
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