Tri-State Spectrum Sensing and Erasure-Injected Probabilistic Inference for Cognitive Radios

Cooperation can significantly improve the diversity order and hence the spectrum sensing accuracy in cognitive radio systems. Since cooperation inevitably introduces communication overhead, question arises as how and how much cooperation should be induced to attain the low-hanging fruits without being excessive and overshadowing the gain. Based on the topology graph, this paper proposes a distributed tri-state probabilistic inference mechanism for cooperative sensing. Conventional decision fusion strategies pull together all the local information (e.g. yes or no for some hypothesis) in the neighborhood, irrespective of its quality. The new idea in the tri-state decision fusion is that if a cognitive radio is rather unsure (up to a threshold) about its sensing result, then instead of sending out this information (which may well be useless anyway), it might as well remain silent, staying in the third state of ``erasure´´ to save energy (and bandwidth). Information-theoretic analysis is conducted to determine the optimal threshold that maximizes the data-rate to energy ratio. Extensive simulations are conducted which confirms the advantages of the tri-state information dissemination strategy.