一种应用于无线传感网的频偏估计改进方法

An improved method of frequency offset estimation for wireless sensor networks

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。

M＆amp;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＆amp;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＆amp;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＆amp;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.