Scenario Classification of Wireless Network Optimization Based on Big Data Technology

With the multi network cooperative development of 4G, 3G and 2G, it is an essential and important task to comprehensively identify and classify the network optimization scenarios in the light of coverage, services, interference, malfunction and resource allocation from geography dimension on each layer, which can directly have an impact on the programs and strategies of network optimization and planning at each level. Meanwhile, precise identification of network optimization scenarios can bring an important guiding significance to the wireless network scheming, planning and optimization. In the network optimization of different scenarios, even with the same network quality, the parameters selection or adjustment during the optimization process may be different, namely, there should be the different parameter optimization models to match to different environments. Based on machine learning and big data technology, this study analyzes the wireless network multi-dimensional attributes and realize the automate identification and classification for cells under different scenarios. As such, the purpose of quantifying and identifying wireless network scenarios can be achieved.