首页 | 本学科首页   官方微博 | 高级检索  
     检索      

低信噪比多径-信道下的OFDM带宽自动估计
引用本文:王炳和,龚安民,曲毅,郭耀廷.低信噪比多径-信道下的OFDM带宽自动估计[J].科学技术与工程,2015,15(30).
作者姓名:王炳和  龚安民  曲毅  郭耀廷
作者单位:武警工程大学 信息工程系,武警工程大学 信息工程系,武警工程大学 信息工程系,武警工程大学 信息工程系
基金项目:国家自然科学基金资助项目《面向空时自适应处理的部分相关波形MIMO雷达关键技术研究》(No.61101238);武警总部课题《便携式频谱监测与管理可视化系统》(WJK-201305)
摘    要:针对低信噪比多径-信道条件下正交频分复用(OFDM)信号带宽估计精度低的问题,提出一种基于小波变换的OFDM信号带宽自动估计方法。首先利用修正周期图法(Welch法)得到信号瞬时功率谱,通过多次观察测量并对功率谱曲线进行统计平均。然后对功率谱曲线进行连续小波变换,计算小波变换后时间-尺度平面上同一时间不同尺度能量累计曲线,提取曲线局部峰值位置,进而估计信号带宽。实验仿真结果表明:在不同多径信道且信噪比为-10dB条件下,估计偏差均不超过1.2%,准确度优于传统方法,且鲁棒性较强。

关 键 词:参数估计  带宽估计  OFDM  连续小波变换
收稿时间:2015/5/15 0:00:00
修稿时间:2015/5/15 0:00:00

Bandwidth Automatic Estimation for OFDM signals at low SNR in multi-path channel
WANG Bing-he,GONG An-min,QU Yi and Guo Yao-ting.Bandwidth Automatic Estimation for OFDM signals at low SNR in multi-path channel[J].Science Technology and Engineering,2015,15(30).
Authors:WANG Bing-he  GONG An-min  QU Yi and Guo Yao-ting
Abstract:To solve the problem of poor performance for orthogonal frequency division multiplexing (OFDM) signals bandwidth blind estimation at low signal-to-noise ratio (SNR) over multi-path channel, a wavelet transformation based signal bandwidth automatic estimation method was proposed. The Welch method was adopted to estimate the instantaneous power spectrum of OFDM signals, and then compute the average signal power spectrum over repeatedly measure and observation. After that, a wavelet transformation is undertaken for the signal power spectrum followed by the computation of the cumulative energy curve of different scales at the same time on time-scale plane. Furthermore, we can extract the local peak location of the curve and estimate the signal bandwidth. The experimental simulation results show that when the signal-to-noise ratio is -10dB over different multi-path channels, the estimation deviation are not more than 1.2%.Compared to the traditional method, our method has higher accuracy and robustness.
Keywords:parameter estimation  bandwidth estimation  OFDM  continuous wavelet transform
本文献已被 万方数据 等数据库收录!
点击此处可从《科学技术与工程》浏览原始摘要信息
点击此处可从《科学技术与工程》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号