UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Convex sensing-reporting optimization for cooperative spectrum sensing Noel, Adam Josiah Gerald


In this thesis, we consider the cooperative spectrum sensing problem in cognitive radio with energy detection. Secondary users with non-identical, independent sensing channels make 1-bit sensing decisions and report their decisions to the secondary base station over orthogonal noisy fading channels. The base station has knowledge of the reporting channel coefficients and acts as a fusion center by combining the decisions with an M-out-of-K rule. We allow the secondary users to trade sensing time slots for additional reporting time slots to increase the signal-to-noise ratios of the reporting channels. We derive the corresponding false alarm and missed detection probabilities, which are functions of the secondary sensor decision thresholds and the durations for sensing and reporting. Furthermore, we bound these probabilities and impose a practical convex region to enable the application of convex optimization for minimization of the false alarm probability for a target missed detection probability. We consider the two cases where the instantaneous and the average reporting channels are known for optimization. Allowing secondary users to trade sensing time slots for additional reporting time slots is shown to significantly improve sensing performance in both cases, even with poor sensing channels and a small number of secondary users.

Item Media

Item Citations and Data


Attribution-NonCommercial-NoDerivatives 4.0 International