A multiple input multiple output (MIMO) neural network equalization algorithm based on channel attention mechanism (MIMO-NNE-CAM) is proposed to address the problem of mode crosstalk in mode division multiplexing optical transmission systems. This algorithm introduces a channel attention mechanism to focus the neural network on more important channel features, achieving effective signal equalization. In order to verify the performance of the algorithm, a the third mock examination mode division multiplexing system is built on the VPI Transmission simulation platform for testing. The experimental results show that, under the condition of a bit error rate (BER) of 1×10^-3, the MIMO-NNE-CAM algorithm achieves performance gains of 1.3 dB and 3.1 dB compared to the original MIMO-NNE and least mean square (LMS) algorithms, respectively. Moreover, it maintains stable bit error rate performance even under strong coupling conditions, demonstrating faster convergence speed and enhanced anti-coupling capability.