摘要
LTE室内深度覆盖是衡量网络质量和影响客户感知的重中之重.准确识别影响楼宇深度覆盖效果的弱覆盖小区一直是室分整改排查工作的难点,传统网优通常需结合大量现场测试与客户投诉识别弱覆盖小区,优化流程长、准确率低且耗费大量资源.本文就当前楼宇弱覆盖整治的问题点,提出了一种基于FAST、MR、TA等多数据源的楼宇弱覆盖小区识别与评估分析方法.依照该方法识别分析重点影响楼宇深度覆盖效果的室分小区并加以整改后,有效改善了覆盖质量并大幅提升了用户体验满意度.
Indoor depth coverage is the key point of the LTE network quality which badly influences customer perception. However, accurate identifi cation of the important weak-coverage indoor cells is always the diffi culty of the following renovation works. Traditional optimization based on customer complaint and much on-site testing always takes long period and is also imprecise and expensive. To solve the above problems, we propose an identifi cation and assessment method for indoor weak-coverage cells based on big data like FAST, MR, TA data. Practical applications prove that the proposed method works well on upgrading the coverage quality and user perception.
作者
何蕊馨
HE Rui-xin(China Mobile Group Design Institute Co.,Ltd. Shaanxi Branch,Shaanxi 710077,China)
出处
《电信工程技术与标准化》
2019年第8期64-68,共5页
Telecom Engineering Technics and Standardization
