Time-varying carrier offset tracking in OFDM systems using particle filtering

被引：9

作者：

Nyblom, T ^{[1
]}

Roman, T ^{[1
]}

Enescu, M ^{[1
]}

Koivunen, V ^{[1
]}

机构：

[1] Helsinki Univ Technol, Signal Proc Lab, SMARAD CoE, FI-02015 Helsinki, Finland

来源：

Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology | 2004年

关键词：

D O I：

10.1109/ISSPIT.2004.1433725

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we address the problem of time varying carrier frequency offset (CFO) estimation for mobile OFDM systems. The offset is modeled using a non-linear state space model. The estimation and tracking is based on a sequential Monte Carlo method called particle filter. Particle filtering is an attractive method because it suits well for nonlinear state-space models and works reliably even if the a posteriori distribution of the state is skewed, multimodal or heavy-tailed. Significant improvement in tracking performance over Extended Kalman Filtering (EKF) solution is shown in simulations.

引用

页码：217 / 220

页数：4

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