Communication Fault Diagnosis Algorithm Based on BP Neural Network

With the development of information technology, we have developed from the ancient flying pigeon transmission and the beacon transmission to the wired telegraph and radio wave in the Republic of China to the 5G era of the three major communication network operators. The development of communication facilities has undoubtedly brought great convenience to our communication. However, due to the application of communication equipment in the high-definition military field and the frequent use in daily life, the complexity of its structure, the diversification of equipment, and the development of large-scale services have caused a lot of troubles for diagnosis. Therefore, the timely diagnosis and repair of communication failures is an important task. Based on this, this article starts from the BP neural network(BNN) and studies the communication fault diagnosis algorithm. This article mainly uses experimental analysis method, personal interview method, questionnaire survey method and qualitative and quantitative analysis method to study the communication fault diagnosis algorithm based on BNN. The experimental research results show that the communication fault diagnosis based on BNN can deal with it effectively and quickly, and speed up the efficiency of fault handling. According to the questionnaire survey, 62% of people support the use of the BP algorithm for fault diagnosis, and 32% believe that the algorithm needs to be improved. Generally speaking, the diagnosis of communication failures must use modern technology for data processing and analysis, and then determine the cause of the failure, so as to provide solutions or intelligently solve the problem.