基于MDT数据的地下场景覆盖问题识别系统设计

地下场景覆盖问题的准确识别一直是网络优化难点,围绕精准定位建立评估模型,以用户轨迹惯性特性为基础完成最小化路测(MDT)数据清洗,采用“基于RSSI测距多点定位算法”和“神经元网络定位技术”相结合方式,完成多维数据关联和迭代矫正模型并纳入指纹库,引入栅格化理念,实现栅格内MDT数据智能汇聚,识别地下场景弱覆盖栅格。本设计能够扩充地下室场景覆盖问题识别的手段。

The design of underground scene coverage problem recognition system based on MDT data

Accurate recognition of underground scene coverage has always been a difficult problem in network optimization. An evaluation model is built around accurate positioning, and MDT data is cleaned base on the inertial characteristics of user trajectory. Multi dimension data association and iterative correction model are completed and incorporated into fingerprint library by combining RSSI based multi-point positioning algorithm and neural network positioning technology Library, the concept of grid is introduced to realize the intelligent aggregation of MDT data in grid and identification the weak coverage grid of underground scene. This design can expand the means of basement scene coverage problem identification.