摘要
鉴于移动通信网规模日益扩大,网络运营状态不易即时掌控的现状,提出了一种用于观测移动网无线信号实时变化的新型监控系统。在该系统长期运行而获得的采样数据基础上,对某处小区的无线信号变化特性进行了研究。运用SPSS统计工具和时间序列中的Box-Jenkins的建模方法,分别建立了AR、MA、ARMA、ARIMA模型对实测数据进行了分析和预测,然后对不同模型的预测结果进行了误差分析,结果表明ARIMA(1,1,1)模型准确性最高,误差最小,能对短期内的无线信号变化趋势进行预测。
As current mobile network develops rapidly, it＇s hard for engineers to immediately control the operating state of the network. Aiming at this problem, this paper presents a novel monitor system for radio signal in mobile network. Moreover, radio signal characteristics in a residential block are studied based on the long-term sampling data obtained using this monitor system. By means of SPSS statistical tools and Box-Jenkins modeling method in time series, some models, such as AR, MA, ARMA and ARIMA, are established to analyze the measured data and predict its trend, then error analysis are carried out for different models. The results show that the model ARIMA （ 1, 1, 1 ） has the highest accuracy, the smallest error, and can forecast the trend of radio signal in short term.
出处
《电子测量与仪器学报》
CSCD
2008年第4期44-48,共5页
Journal of Electronic Measurement and Instrumentation
基金
教育部留学归国人员基金资助项目
