Effective Adaptive Iteration Algorithm for Frequency Tracking and Channel Estimation in OFDM Systems

2010 ◽  
Vol 59 (4) ◽  
pp. 2093-2097 ◽  
Author(s):  
Hong-Yu Liu ◽  
Rainfield Y Yen
Keyword(s):  
Channel Estimation ◽  
Iteration Algorithm ◽  
Ofdm Systems ◽  
Frequency Tracking

scholarly journals Maximum likelihood-based adaptive iteration algorithm design for joint CFO and channel estimation in MIMO-OFDM systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Nan-Hung Cheng ◽  
Kai-Chieh Huang ◽  
Yung-Fang Chen ◽  
Shu-Ming Tseng
Keyword(s):  
Maximum Likelihood ◽  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Carrier Frequency Offset ◽  
Mean Squared Error ◽  
Joint Estimation ◽  
Iteration Algorithm ◽  
Time Varying ◽  
Ofdm Systems ◽  
Mimo Ofdm

AbstractIn this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models.

Channel Estimation and Symbol Detection with ICI Cancellation Based on Superimposed Training for OFDM Systems

2012 ◽  
Vol E95.B (9) ◽  
pp. 2926-2930
Author(s):  
Qinjuan ZHANG ◽  
Muqing WU ◽  
Qilin GUO ◽  
Rui ZHANG ◽  
Chao Yi ZHANG
Keyword(s):  
Channel Estimation ◽  
Ofdm Systems ◽  
Superimposed Training ◽  
Symbol Detection ◽  
Ici Cancellation

A Low-Complexity Sparse Channel Estimation Method for OFDM Systems

2010 ◽  
Vol E93-B (8) ◽  
pp. 2211-2214
Author(s):  
Bin SHENG ◽  
Pengcheng ZHU ◽  
Xiaohu YOU ◽  
Lan CHEN
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Low Complexity ◽  
Ofdm Systems ◽  
Sparse Channel Estimation ◽  
Sparse Channel
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