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Distributed consensus algorithms for decision fusion based cooperative spectrum sensing in cognitive radio

Spectrum sensing is one of the fundamental problems for cognitive radio. In cognitive radio networks, cognitive radios can cooperatively sense the spectrum to detect the presence of primary users with higher sensitivity. This paper proposes distributed consensus algorithms for decision fusion based cooperative spectrum sensing. Both theoretical analysis and simulations are performed to show the convergence property of the algorithms. Results show that the proposed algorithms can realize central OR, AND, and M-out-of-n decision fusion rules by locally exchanging information among each radio and its adjacent neighbors in a distributed way.