Traditional energy-efficient sensor scheduling problems only consider single frequency band in sensor-aided cognitive radio networks. Multi-band energy-efficient sensor scheduling problems have many novel research fields. We formulate a multi-band sensor scheduling problem and propose a genetic algorithm based energy-efficient scheduling algorithm to improve the throughput. We take account of the energy consumption of the sensor when switching frequency bands. In the model, the cognitive base station assigns a set of sensors for each frequency to improve energy efficiency. The genetic algorithm based energy-efficient scheduling algorithm optimally schedules the activities of the sensors to increase the overall secondary system throughput and achieve the goal of energy efficiency. Simulation results show that our algorithm achieves higher network throughput than the greedy algorithm and other algorithms.