Quickest Spectrum Detection Using Hidden Markov Model for Cognitive Radio

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Executive Summary

The prerequisite of accessing white spectrum is to find and locate it. The authors' work deals with spectrum detection and recognition under the umbrella of cognitive radio. In the procedure of spectrum recognition, a frequency sweeping device sweeps the wideband spectrum and the samples of the wideband Power Spectrum Density (PSD) are fed into different Hidden Markov Models (HMMs) sequentially. The core idea of sequential detection or quickest detection is borrowed and utilized here from the classical detection theory. In their proposed approach, forward variables from different HMMs are sequentially exploited to generate the decision statistics. The decision can be made any time as long as the condition is met.

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