Path Selection Strategy of Communication Network Based on Graph Convolutional Neural Network

Abstract

In order to improve the efficiency of communication network path selection, this paper combines the graph convolutional neural network to formulate the communication network path selection strategy and selects the enhanced decoding algorithm as the fixed-point decoding algorithm. For the quantization scheme based on the enhanced decoding algorithm, the selection of the fixed-point integer bit width of each operation variable in the SISO decoder is analyzed and determined by the method of statistical characteristic analysis. Moreover, this paper calculates the normalized threshold value according to the proposed state metric normalization scheme. In addition, this paper constructs an intelligent communication path selection system. Through research, it can be seen that the communication network path selection system based on graph convolutional neural network proposed in this paper can effectively improve the effect of multicommunication path selection.