Hard Decision-based Cooperative Spectrum Sensing via Sequential Detection in Cognitive Radio Networks

This paper presents a study of hard combination data fusion for cooperative spectrum sensing in Cognitive Radio (CR). Fast and accurate spectrum sensing is crucial in realizing a reliable cognitive network. Cooperative spectrum sensing can help reducing the mean detection time and increasing the agility of the sensing process. However, when the number of cognitive users is large, the bandwidth need for the control channel that are used to report the secondary user nodes’ results to the fusion center may become excessively large. This paper presents a hard decision-based cooperative sequential detection scheme to reduce the average sensing time that is required to reach a detection decision. In the scheme, each cognitive radio computes the log likelihood ratio for its every measurement, and quantizes its measurements then sends its hard-decision to base station and the base station sequentially accumulates these log likelihood statistics and determines whether to stop making measurement.

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