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.

scholarly journals Joint Carrier Frequency Offset and Fast Time-Varying Channel Estimation for MIMO-OFDM Systems

2011 ◽  
Vol 60 (3) ◽  
pp. 955-965 ◽  
Author(s):  
Eric Pierre Simon ◽  
Laurent Ros ◽  
Hussein Hijazi ◽  
Jin Fang ◽  
Davy Paul Gaillot ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Carrier Frequency ◽  
Carrier Frequency Offset ◽  
Frequency Offset ◽  
Fast Time ◽  
Time Varying ◽  
Ofdm Systems ◽  
Mimo Ofdm ◽  
Time Varying Channel

SAGE-ML Joint Estimation and Detection Algorithm in MIMO-OFDM Systems

2013 ◽  
Vol 389 ◽  
pp. 494-500
Author(s):  
Jing Peng Gao ◽  
Dan Feng Zhao ◽  
Chao Qun Wu
Keyword(s):  
Maximum Likelihood ◽  
Channel Estimation ◽  
Detection Algorithm ◽  
Joint Estimation ◽  
Ofdm Systems ◽  
Channel State ◽  
Channel Change ◽  
Maximum Likelihood Detection ◽  
System Overhead ◽  
Mimo Ofdm

In order to improve the decoding performance of MIMO-OFDM system in the case of the channel state information is not accurate enough, a new algorithm is proposed, which combines SAGE algorithm, DFT-LS channel estimation and maximum likelihood detection algorithm. The algorithm utilizes joint iterative technology to achieve channel estimation and decoding effect, thereby enhances the reliability of the system. Theoretical study and simulation results show that the proposed algorithm can track the channel change correctly without increasing the system overhead, and the convergence speed is accelerated. Besides, the performance is superior to the commonly used joint detection algorithm. Moreover, comparing with the ideal channel estimation under the maximum likelihood detection algorithm, the new proposed algorithm only has a loss of 0.5dB with the same bit error rate.

scholarly journals Adaptive Blind Channel Estimation for MIMO-OFDM Systems Based on PARAFAC

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Ruo-Nan Yang ◽  
Wei-Tao Zhang ◽  
Shun-Tian Lou
Keyword(s):  
Channel Estimation ◽  
Cost Function ◽  
Orthogonal Frequency Division Multiplexing ◽  
Weighted Least Squares ◽  
Estimation Method ◽  
Blind Channel Estimation ◽  
Ofdm Systems ◽  
Blind Channel ◽  
Mimo Ofdm ◽  
The Cost

In order to track the changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is prior to estimate channel impulse response adaptively. In this paper, we proposed an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weight the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of third-order tensor which consists of the weighted OFDM data symbols. To reduce the computational load, we adopt a recursive singular value decomposition method for tensor decomposition; then, the channel parameters can be estimated adaptively. Simulation results validate the effectiveness of the proposed algorithm under diverse signalling conditions.

Time and Frequency Synchronization for MIMO-OFDM Systems

2013 ◽  
Vol 321-324 ◽  
pp. 2888-2891
Author(s):  
Jing Peng Gao ◽  
Chao Qun Wu ◽  
Dan Feng Zhao
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Carrier Frequency Offset ◽  
Time Synchronization ◽  
Multiple Input Multiple Output ◽  
Frequency Offset ◽  
Time Instant ◽  
Frequency Synchronization ◽  
Ofdm Systems ◽  
Frequency Offset Estimation ◽  
Mimo Ofdm

Any carrier frequency offset will cause a loss of subcarrier orthogonality which results in ICI and hence performance degrades severely in MIMO-OFDM systems. In this paper, a time and frequency synchronization solution for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed. The synchronization is achieved using one Constant Amplitude Zero Auto Correlation (CAZAC) sequence-based preamble which is simultaneously transmitted from all transmit antennas in the same OFDM time instant. The synchronization is accomplished sequentially by coarse time synchronization, fractional frequency offset estimation, integral frequency offset estimation and fine time synchronization. The simulation shows that the proposed algorithm can estimate the timing and frequency offsets efficiently in MIMO-OFDM systems, especially in low signal-to-noise ratio condition.

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