Abstract: For wireless sensor networks (WSN) scenarios with energy harvesting, sensors regularly send status update information to the base station, but limited by spectrum resources, only a small number of sensors are allowed to send in a given time slot. At the same time, the transmission power is limited by the remaining energy. In view of the above problems, we propose a state update strategy scheme based on the Markov Decision Process (MDP) of the Age of Information(AoI). The model depicts the intrinsic relationship between the spectrum, energy, and transmission time slots in the WSN. In order to solve the problem of high computational complexity in large-scale sensor networks, a scheduling algorithm based on Whittle Index is proposed. This algorithm obtains asymptotically optimal performance through iteration, and the computational complexity is significantly reduced compared to large-scale MDP solutions, taking into account the real-time and accuracy of scheduling.