摘要
依据时间序列理论,重点考虑CDMA的固有网络特性,提出了一种连续的预测模型。该模型根据CDMA网络小区的非平稳时间序列接入特点,建立了一种基于历史数据与采样数据相互补充的预测模式。为了提高模型的收敛性,根据偏微分方程的最大值对采样数据进行平滑处理。该模型充分考虑了CDMA网络运行的周期性、随机性以及突发性,可获得良好的自适应性,较好地消除了突变数据的影响。该模型可以及时准确预测一段时间内的网络负载,确定参数调整方案,提前调整QoS参数,预防性的均衡系统负载能防止QoS效果出现大的抖动,提高接入率。试验结果表明,该模型能够以较小的计算代价有效提高CDMA网络的QoS性能。
A continuous predictive model based on time sequence theory and the connatural characteristic of CDMA was presented. According to the unsteady time sequence access feature of CDMA cell, a predictive mode depending on mutually complementary historical data and sampled data was established by this model.In order to improve the convergence of the model the sampled data was smoothed according to the extremum made by the partial differential equation.Through the full consideration of the periodic,random and bursting properties in operation of CDMA network, the model had got good performance in self-adaption and could eliminated the influence of the burst data to a certain extent.The model has the ability of predicting the network load accurately for a certain period of time,so the QoS parameters can be adjusted in advance,and hence avoid the dithering of the sysem and enhance the successful access rate.Experiment results show that this model can increase effectively the QoS performance of the CDMA network with smaller calculating cost.
出处
《吉林大学学报(工学版)》
EI
CAS
CSCD
北大核心
2004年第1期16-19,共4页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金资助项目(60275626).