摘要
传统的移动网络中忙时检测方法多数用统计的方法估计出语音业务的忙时,数据业务引入后,数据业务和语音业务的忙时还存在时间差,仍用统计的方法既浪费时间又估计不准确,利用条件相对熵的原理对原有的忙时检测算法进行改进,改进后的算法可以不受观测次数的限制,计算出条件相对熵的值对EDGE网络数据进行分析,得出忙时,提出算法具有计算速度快、精度高、不受观测次数的限制等优点,能够更好的管理和检测忙时,为网络优化提供依据。
The traditional busy-time detection algorithm mostly adopts statistical method in estimating the busy time of vice service.With the introduction of data service,the data service and voice service are different in busy time,and the statistical method becomes time-wasted and its estimation is not also accurate.With the principle of relative entropy,the original busy-time detection algorithm is improved,and the improved algorithm,not limited by observation number,could calculate the value of relative entropy conditions on EDGE network,analyze data,and acquire the busy time.It could also have better management and detection of busy time,and thus provide a foundation for network optimization.
出处
《通信技术》
2011年第10期86-87,共2页
Communications Technology
基金
中国移动新疆分公司研究发展基金项目(No.xjm2010-1)
关键词
忙时检测
熵
相对熵
条件相对熵
网络优化
busy-time detection
entropy
relative entropy
conditional entropy
network optimization
