Deep Learning-Based Method for 5G Micro-Base Station Signal Identification

The State Council's latest Guidance on Actively Promoting “Internet +” emphasizes that “the development of a new generation of mobile communication networks and the next generation of the Internet should be accelerated”, and the construction of 5G base stations has become a top priority in this new era. However, the current 5G signal has problems such as high coverage duplication rate. This paper proposes an intelligent 5G micro-base station signal identification method based on deep learning. Combining infrared imaging technology and machine learning technology, the deep learning algorithm can effectively reduce the duplicated coverage and the number of base stations installed in some areas, so as to reduce the waste of power caused by the idle power consumption of base stations and enhance the 5G signal strength.