In order to obtain a higher signal-to-noise ratio, the transmitted power of nodes will be improved, wireless sensor networks work in dynamically changing channel conditions and interference levels environments at the same time, causing the interference between the nodes to increase, the node will continue to increase the transmit power to offset the negative impact, which will lead to a gradual deterioration of the network environment and waste too much node energy. Aiming at the above problems, this paper proposes a wireless sensor network power control strategy under cooperative game. In order to enable the node to dynamically adjust the transmit power according to the surrounding environment information, the algorithm introduces the distance between nodes as the interference weight factor to correct the effective interference model. The signal-to-noise ratio model is improved. Based on the cooperative game theory, the node information transmission rate and its residual energy are integrated, and the utility function under the cooperative game is established. The normalized information transmission rate and the transmission power variance value under different utility weight factors are used. After the four balances of the signal-to-noise ratio and the network utility are comprehensively weighed, the appropriate utility weight factor value is obtained, and the utility function has a Nash equilibrium solution. After several iterations of the algorithm, the optimal transmission power set of the whole network is obtained. The simulation results show that the optimal transmit power variance obtained by the algorithm is small, and the algorithm converges fast. The network can obtain a higher signal-to-noise ratio when the node has lower transmit power, and the network life cycle can be extended to achieve higher performance. The nodes utility can be improved.