Cooperative Bayesian-based detection framework for spectrum sensing in cognitive radio networks

Cooperative Bayesian-based detection framework for spectrum sensing in cognitive radio networks

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In this study, a cognitive radio network is considered in which multiple secondary users intend to detect a primary user frequency band in order to specify whether it is occupied or not. To this end, a blind Bayesian framework is proposed by which secondary users cooperatively perform spectrum sensing. In practice, it is impossible to estimate the noise variance accurately (noise uncertainty problem) and this can degrade the performance of some previous spectrum sensing algorithms like energy detection (ER). To overcome this issue, unlike the conventional ER, the proposed algorithm utilises marginalisation to eliminate the effect of uncertainty in noise variance estimation. By computer simulations using MATLAB, it can be seen that the authors' algorithm reaches the ideal case for by improving the level of cooperation (increasing the number of secondary users) and yet its is also improved compared to ER in practical situations (presence of noise uncertainty).


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