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We investigate spectrum sensing by energy detection based on two different objective functions: a Bayesian sensing cost or the network weighted sum capacity. The Bayesian cost is a traditional detection measure which aims at minimizing a combination of the miss-detection and false-alarm probabilities, while the capacity objective is a communication measure which aims at maximizing the network throughput...
We develop a closed-form optimal spectrum sensing threshold to maximize a cognitive network weighted sum capacity. In an one primary user and one cognitive user network, spatial location side information is used by the cognitive transmitter to adjust its sensing threshold accordingly. Numerical results show that, compared to another threshold based on minimizing a Bayesian risk function, the proposed...
We study Bayesian detection based cognitive sensing and analyze its impact on the capacity in various cases of location information. In a network of one primary and one cognitive users, the cognitive transmitter relies on information about the locations of the primary transmitter and the two receivers to design its optimal sensing threshold. Results show that this location-aware threshold can significantly...
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