摘要
针对电力噪声和正交频分复用(orthogonal frequency division multiplexing,OFDM)信号的特点,为提高检测的准确度同时减少数据冗余,基于含噪信号本元分析,分解干净信号和电力噪声特征向量,根据噪声和信号空间能量的不同,利用本元滤波的方法检测数据分组的起点。在电力噪声和基于G3方案的OFDM模型下,通过对经典延时相关检测算法和本元滤波检测算法进行性能评测比较,结果显示在不同信噪比下,本元滤波检测算法对接收信号的起点检测更准确,相应系统的误码率得到降低。
Considering the characteristics of power line noise and orthogonal frequency division multiplexing （OFDM） signal, a principal component analysis （PCA） was proposed for improving the accuracy of detection. This algorithm decomposes noisy signal into its principal components along the axes of a vector space of clean speech. To obtain the packet detection, the principle component filter was used： Through the evaluation to classic delay-and-correlate algorithm and the principle component filter algorithm for packet detection were compared. The results show that the principle component filter algorithm is more accurate for the OFDM signal detection, therefore, the algorithm can decrease the bit error rate （BER） of the system effectively.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第7期2510-2516,共7页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(61172089)
高等学校博士学科专项科研基金资助项目(20120161120012)
湖南省科技计划项目(2014WK3001)~~
关键词
电力线通信
正交频分复用
本元分析
power line communication
orthogonal frequency division multiplexing
principal component analysis
