Cooperative spectrum sensing via sequential detection for cognitive radio networks
Efficient and reliable spectrum sensing plays a critical role in cognitive radio networks. This paper presents a cooperative sequential detection scheme to minimize the average sensing time that is required to reach a detection decision. In the scheme, each cognitive radio computes the Log-Likelihood ratio for its every measurement, and the base station sequentially accumulates these Log-Likelihood statistics and determines whether to stop making measurement. The average number of required samples depends on the Kullback-Leibler distance between the distributions of the two hypotheses under test. This suggests a criterion for selecting the most efficient radios to facilitate spectrum sensing. The paper also studies how to implement the scheme in a robust manner when the assumed statistical models have uncertainties. These ideas are illustrated through an example that assumes both the signal and noise are Gaussian distributed.
Zou, Qiyue, Songfeng Zheng, and Ali H. Sayed. "Cooperative spectrum sensing via sequential detection for cognitive radio networks." In 2009 IEEE 10th Workshop on Signal Processing Advances in Wireless Communications, pp. 121-125. IEEE, 2009.