Optimization of probability of error in collaborative spectrum sensing of time-limited cognitive radio networks

We study the probability of error optimization problem in collaborative spectrum sensing (CSS) with limited time resources in cognitive radio (CR) networks. The frame structures for sensing and data transmission, if the spectrum is identified as vacant, are both assumed fixed. This implies that the time resource dedicated for CSS is limited and shared between spectrum sensing time and results reporting time, which depends on the number of sensing users. We consider an optimization problem containing network constraints on time resources for secondary users (SUs) which cooperate with each other using a weighted fusion rule. It is assumed that the SUs are in energy-surplus regime and a predefined constraint on probability of collision is satisfied to protect the cooperative network performance. We analytically prove the convexity of the optimization problem to ensure obtainability of a global solution. Analytical results, in addition to simulation results, are provided to prove the claims.