Optimal Wideband Spectrum Sensing Framework for Cognitive Radio Systems

An optimal wideband spectrum sensing framework which identifies secondary transmission opportunities over multiple nonoverlapping narrowband channels is presented. The framework, which is referred to as multiband sensing-time-adaptive joint detection, improves the overall secondary user performance while protecting the primary network and keeping the harmful interference below a desired low level. Considering a periodic sensing scheme, the detection problem is formulated as a joint optimization problem to maximize the aggregate achievable secondary throughput capacity given a bound on the aggregate interference imposed on the primary network. It is demonstrated that the problem can be solved by convex optimization if certain practical constraints are applied. Simulation results attest that the proposed wideband spectrum sensing framework achieves superior performance compared to contemporary frameworks. An efficient iterative algorithm which solves the optimization problem with much lower complexity compared to other numerical methods is presented. It is established that the iteration-complexity and the complexity-per-iteration of the proposed algorithm increases linearly as the number of optimization variables (i.e., the number of narrowband channels) increases. The algorithm is evaluated via simulation and is shown to obtain the optimal solution very quickly and efficiently.