Parallel Cooperative Spectrum Sensing Based on Genetic Algorithm for Heterogeneous Multi-channel Cognitive Network ?

To sense the spectrum efficiently in heterogeneous multi-channel and multi-user cognitive network, a parallel cooperative spectrum sensing strategy based on genetic algorithm is proposed. It defines the expression of system utility considering the transmission gain and sensing overhead, and protects the primary user network by introducing the penalty function. To obtain the largest system utility, it uses genetic algorithm to obtain the optimal assignment between multiple channels and multiple secondary users. The simulation results show that the proposed strategy can obtain higher system utility and require less cooperative secondary users than improved iterative Hungarian algorithm based strategy, greedy based strategy and random cooperative sensing strategy.