In order to meet the real-time field and repeatable detection requirements for the signal coverage effectiveness of wireless communication network, a distributed wireless coverage detection algorithm based on wireless sensor network was proposed. The received signal strength of the wireless communication network was perceived and preprocessed by wireless sensor nodes randomly deployed in the target area. The variogram was used to construct a new BP(back propagation) neural network objective function, and the initial weight and threshold were optimized by the modified particle swarm algorithm. The trained network model was used to estimate the interpolation of the target area with detection blind zone, and the data collected by the sensor nodes were combined to generate the equal signal strength line of the wireless communication network. The simulation results show that the proposed algorithm has higher prediction accuracy than other classical algorithms, and can effectively detect the signal coverage situation of the wireless communication network in the target area.