基于空时压缩感知算法的蜂窝流量预测
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摘要
针对蜂窝网络中,基站发射功率不能有效根据小区内峰值流量实时调整而造成蜂窝网络能量浪费这一问题,提出一种基于阈值控制的正则化正交匹配追踪(BT-ROMP)蜂窝流量预测算法。该算法利用小区内用户行为在时间与空间上的周期平稳变化特性,构建蜂窝流量块稀疏模型;利用阈值有效筛选出正则化漏掉的次优原子,扩大原子候选集,达到减少算法迭代次数与提高重构精度的目的。仿真结果表明,本文算法较正则化正交匹配追踪算法(ROMP),算法预测精度平均提高0. 01。
A cellular network traffic prediction algorithm based on Threshold Regularized Orthogonal Matching Pursuit( BTROMP) is proposed to solve the problem of cellular network energy waste,where Bases transmitted power cannot be effectively adjusted according to the peak flow rate in cells. The block sparse model of cellular traffic is constructed by using the characteristics of periodic and stable changes. And the algorithm uses the threshold to effectively screen the suboptimal atoms which are regularized,and to expand the candidate set to reduce the number of iterative times and improve the accuracy of the reconstruction.Simulation results show that compared with regularized orthogonal matching pursuit algorithm( ROMP),the prediction accuracy of the proposed algorithm can be improved by 0. 01 on average.
A cellular network traffic prediction algorithm based on Threshold Regularized Orthogonal Matching Pursuit( BTROMP) is proposed to solve the problem of cellular network energy waste,where Bases transmitted power cannot be effectively adjusted according to the peak flow rate in cells. The block sparse model of cellular traffic is constructed by using the characteristics of periodic and stable changes. And the algorithm uses the threshold to effectively screen the suboptimal atoms which are regularized,and to expand the candidate set to reduce the number of iterative times and improve the accuracy of the reconstruction.Simulation results show that compared with regularized orthogonal matching pursuit algorithm( ROMP),the prediction accuracy of the proposed algorithm can be improved by 0. 01 on average.
引文
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[2]周厦.EPON与Wi MAX融合接入网节能技术的研究[D].南京:南京邮电大学,2014.
[3]张志才.Femtocell网络的绿色节能技术研究[D].北京:北京邮电大学,2014.
[4]RENGARAJAN B,RIZZO G,AJMONE MARSAN M.Energy-optimal Base Station Density in Cellular Access Networks with Sleep Modes[M].Elsevier North-Holland Inc.,2015.
[5]李荣鹏.面向绿色蜂窝网的流量预测分析与智能化基站管理策略研究[D].杭州:浙江大学,2015.
[6]文倩.结构化压缩感知在无线通信网络流量预测中的应用研究[D].杭州:浙江大学,2013.
[7]危彦.蜂窝网络中基于流量预测的节能关键技术研究[D].杭州:浙江大学,2012.
[8]WANG Z,ZHANG W.A separation architecture for achieving energy-efficient cellular networking[J].IEEE Transactions on Wireless Communications,2014,13(6):3113-3123.
[9]LI R,ZHAO Z,ZHOU X,et al.Energy savings scheme in radio access networks via compressive sensing-based traffic load prediction[J].European Transactions on Telecommunications,2014,25(4):468-478.
[10]刘迪迪,林基明,王俊义,等.蜂窝网络中能量收集基站的能量协作算法[J].上海交通大学学报,2018,52(3):365-372.
[11]王科平,杨赞亚,恩德.基于分类冗余字典稀疏表示的图像压缩方法[J].计算机工程,2017,43(9):281-287.
[12]魏东,周健鹏.K-SVD和OMP算法在超声信号去噪中的应用[J].应用声学,2016,35(2):95-101.
[13]AND J D R,MOORE J S.ROMP reactivity of endo-and exo-dicyclopentadiene[J].Macromolecules,2015,35(21):7878-7882.
[14]黄志清,张严心,李梦佳,等.基于St OMP算法的WSN压缩感知数据重构[J].计算机工程,2017,43(9):149-155.
[15]吴国辉,张华栋,李兴坤,等.基于改进测量的FR-CoSa MP图像重建算法[J].计算机工程与设计,2016,37(6):1555-1559.
[16]任晓馨.压缩感知贪婪匹配追踪类重建算法研究[D].北京:北京交通大学,2012.
[17]WANG A,WANG Y,JIANG L.Improved sparse channel estimation for multi-user massive MIMO systems with compressive sensing[C]//International Conference on Wireless Communications&Signal Processing.2015:1-5.
[18]李永刚,岳文涛,李龙江.一种TD-LTE与e HRPD系统重叠覆盖下的负载均衡算法[J].计算机与现代化,2017(5):5-9.
[19]董袁泉,王浩.基于离散鸡群压缩感知的WSNs多目标定位[J].计算机与现代化,2017(12):23-27.