C-RAN中基于Markov模型的小区用户数预测

Research on the Prediction of the Number of Cell Users Based on Markov Model in C-RAN Network

基于排队论和Markov转移模型,对C-RAN(绿色无线接入网)中小区簇所包含所有小区的用户数的变化规律进行预测研究。提出了一种综合考虑历史规律及当前趋势的预测方案,对各小区不同时刻的用户到达率和离开率进行预测。通过求Markov转移模型的瞬态解,得出各小区用户数在不同时刻的统计平均值。在考虑预测误差和系统开销的情况下,求解最优的预测周期。仿真结果表明,较优的预测周期能客观反映实际环境中用户数的变化规律。

In this paper, the variation of the number of cell＇s users within the cluster is studied based on Queuing theory and Markov transition model in C-RAN network. We proposes a prediction scheme to calculate the cell＇s arriving rate and leaving rate by considering the history regular and the current trend. By solving the transient solution of the Markov transition model, the statistical average of the every cell＇s users is achieved at different times. Considering the prediction error and the system o- verhead, the optimal period of the prediction is obtained. The simulation result shows that better prediction period can accu- rately reflect the variation of the users in the realistic environment.