现代电子技术
現代電子技術
현대전자기술
MODERN ELECTRONICS TECHNIQUE
2014年
5期
35-38
,共4页
频偏估计%信噪比门限%自相关函数%M&M算法
頻偏估計%信譟比門限%自相關函數%M&M算法
빈편고계%신조비문한%자상관함수%M&M산법
frequency offset estimator%SNR threshold%autocorrelation function%M&M method
为解决频偏估计中经典的M&M算法在频偏增大时信噪比门限变差的问题,提出一种改进的频偏估计算法。首先对自相关函数做预平均处理来降低噪声,然后利用预平均值做频偏粗估计,并利用粗估计值纠正相位来减轻相位模糊的问题,最后推导更加合理的窗函数并给出最终频偏估计表达式。仿真表明该算法的信噪比门限比M&M算法至少低-1 dB,且在频偏加大时仍然能保持较低的信噪比门限。在保证-3.5 dB的信噪比门限的前提下该算法的估计范围达到了理论值的90%,另外在最大自相关阶数较小时,估计精度门限优于M&M算法。该算法在M&M算法基础上的改进达到了预期效果,能同时满足无线传感网频偏估计中对低信噪比门限和大估计范围的要求。
為解決頻偏估計中經典的M&M算法在頻偏增大時信譟比門限變差的問題,提齣一種改進的頻偏估計算法。首先對自相關函數做預平均處理來降低譟聲,然後利用預平均值做頻偏粗估計,併利用粗估計值糾正相位來減輕相位模糊的問題,最後推導更加閤理的窗函數併給齣最終頻偏估計錶達式。倣真錶明該算法的信譟比門限比M&M算法至少低-1 dB,且在頻偏加大時仍然能保持較低的信譟比門限。在保證-3.5 dB的信譟比門限的前提下該算法的估計範圍達到瞭理論值的90%,另外在最大自相關階數較小時,估計精度門限優于M&M算法。該算法在M&M算法基礎上的改進達到瞭預期效果,能同時滿足無線傳感網頻偏估計中對低信譟比門限和大估計範圍的要求。
위해결빈편고계중경전적M&M산법재빈편증대시신조비문한변차적문제,제출일충개진적빈편고계산법。수선대자상관함수주예평균처리래강저조성,연후이용예평균치주빈편조고계,병이용조고계치규정상위래감경상위모호적문제,최후추도경가합리적창함수병급출최종빈편고계표체식。방진표명해산법적신조비문한비M&M산법지소저-1 dB,차재빈편가대시잉연능보지교저적신조비문한。재보증-3.5 dB적신조비문한적전제하해산법적고계범위체도료이론치적90%,령외재최대자상관계수교소시,고계정도문한우우M&M산법。해산법재M&M산법기출상적개진체도료예기효과,능동시만족무선전감망빈편고계중대저신조비문한화대고계범위적요구。
M&M method is a typical frequency offset estimator,but its SNR threshold raises when frequency becomes larger, to solve this problem,an improved frequency offset estimator based on M&M method is proposed. Firstly the average treatment of the autocorrelation function is utilized to reduce the noise. Then frequency offset is roughly obtained by using average value, and the problem of phase ambiguity is solved. At last a more reasonable window function is derived and the final expression of estimation frequency offset is given. Simulation results show that the SNR threshold of the proposed method is at least-1 dB low-er than M&M method,and the SNR threshold can keep low when the frequency offset increases. The estimation range of the pro-posed method can reach 90% of the theory value in condition of keeping the SNR threshold -3.5 dB. Additionally,the estima-tion accuracy is better than M&M method when max autocorrelation order is small. The proposed method meets the requirements both in SNR threshold and estimation range in wireless sensor networks.