Cognitive Sensing Based on Side Information

We study a sensing algorithm for cognitive radios based on Bayesian energy detection while utilizing available side information. The side information available to the cognitive user can consist of: (i) spatial locations of the cognitive and primary receivers, (ii) received power of the primary-signal at the cognitive user, and (iii) a priori transmission probability of the primary user. Considering several scenarios with different combinations of side information, we derive the respective, optimal detection thresholds for the cognitive user. Numerical results using these thresholds show significant performance improvement based on the side information. Specifically, information on spatial locations can help stabilize the performance for a wide range of the primary activity factor. Highly skewed a priori primary-transmission probability further helps improve the performance dramatically.