摘要
针对电力线通信网络信号载波频率估计问题,文中将其转化为模式识别问题,并导出了最小二乘支持向量机(LS-SVM)估计器。该估计器可以有效地对信号载波频率进行估计且不需要观测数据的统计知识,并且估计性能对载波相位不敏感。仿真结果表明,在低信噪比下,由于基于分类的方法不具有非线性估计的阈值效应,因此与传统的最大似然估计(LM)方法相比,所提出的估计方法具有更好的性能。
For the problem of signal carrier frequency estimation in power line communication network,this paper transforms it into pattern recognition problem and derives the least square support vector machine( LS-SVM) estimator. The estimator can effectively estimate the signal carrier frequency without statistical knowledge of the observed data,and the estimated performance is insensitive to the carrier phase. The simulation results show that the proposed estimation method has better performance than the traditional maximum likelihood estimation( LM) method at low SNR,because the classification-based method does not have the threshold effect of nonlinear estimation.
作者
冯驰
吴丽莎
张凯
李超
FENG Chi;WU Li-sha;ZHANG Kai;LI Chao(State Grid Anhui,Anqing power supply company,Anqing 246003,Anhui Province,China)
出处
《信息技术》
2019年第1期103-107,共5页
Information Technology
