The efficient use of spectrum has become an active research area due to its scarcity and underutilization. In a spectrum sharing scenario as cognitive radio (CR), the vacancy of licensed frequency bands could be detected by a secondary user through spectrum sensing techniques. Usually, this sensing approaches are performed with prior knowledge of the channel features. In the present work, a blind spectrum sensing approach based on independent component analysis (ICA) and singular spectrum analysis (SSA) is proposed. The approach is tested and compared with other outcomes. Results show that the proposed scheme is capable of detecting most of the sources with low time consumption, which is a remarkable aspect for online applications with demanding time issues.
In this paper it is found that, regardless of the statistics of the input, the derivative of the relative entropy over the Binomial channel can be seen as the expectation of a function that has as argument the mean of the conditional distribution that models the channel. Based on this relationship we formulate a similar expression for the mutual information concept. In addition to this, using the connection between the Binomial and Poisson distribution we develop similar results for the Poisson channel. Novelty of the results presented here lies on the fact that, expressions obtained can be applied to a wide range of scenarios.
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