Joint Iterative Detector and Decoder Channel Estimation Based on Extended Kalman Filter
LIAO Yong1,2, SHEN Xuan-fan1, DAI Xue-wu3, ZHOU Xin1, WANG Dan4
1. Center of Communication and TT & C, Chongqing University, Chongqing 400044, China;
2. The State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, Shaanxi 710071, China;
3. State Key Laboratory of Synthetical Automation for Process Industry, Northeastern University, Shenyang, Liaoning 110819, China;
4. Chongqing Key Laboratoty of Mobile Communications Technology, Chongqing University of Posts and Telecommunication, Chongqing 400065, China
Abstract：In high-speed environment,fast fading and non-stationary limits the channel estimation performance,so we proposed a channel estimation method for high-speed mobility in downlink.The time-varying channel was modeled as an autoregressive (AR) process.So that a self-feedback extended Kalman filter (EKF) was set up to track the channel response and AR parameter.In order to eliminate the influence of error propagation in self-feedback EKF,an iterative detector & decoder receiver was adopted,by utilizing the redundancy of encoding,to improve the estimation accuracy.The simulation results show that compared with least squares (LS) and linear minimum mean square errors(LMMSE) in high speed environment,the proposed method improves the channel estimation accuracy and performance of whole system.And it could be applied to baseband signal processing of wireless receiver in high-speed train.
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2018, Vol. 46 
