Opportunistic Spectrum Access in Cognitive Radios (CRs) calls for efficient and accurate spectrum sensing mechanism that provides the CR network with current spectral occupancy information. For a CR using energy detection for spectrum sensing, exact knowledge of Signal to Noise Ratio (SNR) at the receiver is crucial for determination of the decision threshold. This threshold in turn determines the probability of error (Probability of missed detection and probability of false alarm). In this paper, an innovative technique is proposed wherein spectral occupancy decisions from different CRs are combined and used as a training signal to adapt the local decision threshold. Each CR trains itself such that its decision is in alignment with other CRs in the network. Same can be looked at from group intelligence perspective where, multiple users, each with incomplete information, can learn from the group’s wisdom to reach a supposedly correct conclusion. Simulations under Rayleigh fading show probability of error at par with other co-operative spectrum sensing techniques albeit at lower complexity levels. We also probe into the accuracy of those decisions with standard techniques from a Cognitive Network perspective to prove the wisdom in group knowledge.
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