In cognitive radio networks the secondary users are allowed to seek and exploit the under-utilized segments of the frequency spectrum. Driven by the ongoing growth of data networks in scale and traffic demands, the frequency spectrum will be populated by frequent opportunistic access by the cognitive users. Hence, the spectrum opportunities become rare and scattered across the entire spectrum. Due to their transient nature, such rare spectrum opportunities should be identified quickly. This paper develops a data-adaptive search algorithm for identifying such rare spectrum opportunities quickly and reliably.
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