This article proposes a channel equalization neural network based on InceptionNet for the channel equalization of a single-carrier MIMO system. This scheme does not require statistical channel information and directly uses the received pilot signals for offline training. It uses improved convolution neural network extracts features so that it can learn the channel information features contained in the pilot signal and then equalize the channel through the neural network, making the model output the equalized signal. The simulation results show that compared with the traditional channel equalization method, the network model proposed in this paper has better performance in reducing the signal error rate.