超奈奎斯特信号载波频偏估计的梯度下降算法

Gradient Descent Algorithm for Frequency Offset Estimation of Faster-Than-Nyquist Signal

超奈奎斯特(Faster-than-Nyquist,FTN)传输技术是一种基于时域压缩的信号调制技术,具有更高的传输速率及频带利用率,但是却引入了无限长的码间串扰(inter-symbol interferences,ISIs),这对载波频偏估计提出了新的挑战。对于FTN信号的频偏估计,传统算法在门限和精度等方面都有所下降。本文将梯度下降算法应用到载波频偏估计中,通过迭代搜索的方式,获得对频偏的精确估计。估计过程中直接通过数据部分进行估计,不需要借助额外的导频序列。仿真结果表明,梯度下降法与传统算法在性能上相比有了较好的改善,虽然具有较多的迭代次数和运算量,但是却能够较好地适应FTN信号的特性。梯度下降法不仅在门限范围内更靠近克拉美罗界(Cramer-Rao bound,CRB),而且在整个频段上具有更稳定的性能。

Faster-than-Nyquist （FTN） signaling is a kind of signal modulation technique, which is based on the compres- sion in time domain and could achieve higher transmission rate and bandwidth efficiency. However, it would introduce infi- nite inter-symbol interferences （ISis）, which would bring a new challenge for carrier frequency offset estimation. The per- formance of traditional estimators would reduce in b＇q＇N signaling system. In this paper, the gradient descent algorithm would be applied to carrier frequency offset estimation. Without the aid of extra pilot, the unbiased estimation can be ob- tained by multiple iterative searches. Numerical simulation results indicate that gradient descent estimator has better per- formance than traditional estimators. Although it needs multiple iterations and more calculation, it could adapt to the char- acteristic of FTN signal better. The performance of decent gradient estimator is closer to Cramer-Rao bound （ CRB）, and it also has a good stability in all frequency offset regions.