Binary Consensus for Cooperative Spectrum Sensing in Cognitive Radio Networks
In this paper, the authors propose to use binary consensus algorithms for distributed cooperative spectrum sensing in cognitive radio networks. They propose to use two binary approaches, namely diversity and fusion binary consensus spectrum sensing. The performance of these algorithms is analyzed over fading channels. The probability of networked detection and false alarm are characterized for the diversity case. They then show that binary consensus cooperative spectrum sensing is superior to quantized average consensus in terms of agility, given the same number of transmitted bits.