Abstract: Aiming at the problems of long block propagation time and poor blockchain network topology transmission performance in the current blockchain network, this paper designs an improved neighbor node optimization strategy based on Monte Carlo method. Firstly, the strategy calculates the score between a node and its neighbor node by the time of each round of blocks arriving at the node. Then, the strategy randomly adds new nodes from the candidate nodes into the neighbor set of the current nodes according to the elimination rate of the current neighbor nodes, and the strategy calculates all possible elimination combinations. The strategy then uses Monte Carlo method and Softmax function to obtain the probability that each combination may be eliminated. Finally, the strategy randomly selects nodes from the network to replace the current neighbor nodes according to the probability of elimination of the current neighbor nodes. The simulation experiments show that, compared with the strategy of randomly selecting neighbor nodes, the neighbor node optimization strategy can improve the propagation efficiency of blocks in the blockchain network, which reduces the average propagation time of the blocks by about 30%.