A Novel Noise Suppression Channel Estimation Method Based on Adaptive Weighted Averaging for OFDM Systems

Ming-tong, Zhang; Zhou, Xiao; Wang, Chengyou

doi:10.3390/sym11080997

Cited by 15 publications

(18 citation statements)

References 38 publications

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“…However, in the time-varying channel, the Doppler spread will bring Doppler distortion in the averaging process. Although the multi-frame averaging method with more average frames can obtain better noise suppression ability, the Doppler distortion caused by it will be more serious [45]. Therefore, the average frame number is a crucial parameter for the multi-frame averaging method and should be carefully determined.…”

Section: B Related Workmentioning

confidence: 99%

“…According to the research of Zhang et al [45], a suitable choice of the average frame number is related to the Doppler spread and the operating SNR in the time-varying channel.…”

Section: B Related Workmentioning

confidence: 99%

“…For ease of notion without losing generality, this paper drops the antenna index in subscript when next to illustrate the channel estimation method, and the CIR LS estimate LŜ () n h at the nth OFDM symbol can be expressed as [45]:…”

Section: Time-domain Ls Channel Estimationmentioning

confidence: 99%

“…The estimation of d f is investigated in [45], and it is based on the fact that the autocorrelation function of the received pilot symbols is the same as that of the CIR, i.e.…”

Section: ) Estimation Of Unknow Parametersmentioning

confidence: 99%

“…, and then let that j be z. Then, the first zero crossing point 0 z of () j  can be calculated as [45]:…”

Section: ) Estimation Of Unknow Parametersmentioning

confidence: 99%

See 4 more Smart Citations

Time-Varying Sparse Channel Estimation Based on Adaptive Average and MSE Optimal Threshold in STBC MIMO-OFDM Systems

2020

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Channel estimation is still a challenge for space time block coding (STBC) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems in time-varying environments. To estimate the channel state information (CSI) precisely without increasing complexity in any significant way, this paper utilizes the sparsity and the inherent temporal correlation of the time-varying wireless channel, and proposes a novel channel estimation method applied to STBC MIMO-OFDM systems. The proposed method consists of two schemes: adaptive multi-frame averaging (AMA) and improved mean square error (MSE) optimal threshold (IMOT). First, the temporal correlation of the time-varying channel is modeled by a linear Gauss-Markov (LGM) model, and the AMA scheme is incorporated to refine the initial estimated channel impulse response (CIR) through noise reduction. Based on the LGM model, the optimal average frame number is adaptively determined by minimizing the MSE of the denoised CIR. Then, the sparsity of the wireless channel is utilized to model the CIR as a sparse vector, and the IMOT scheme is performed to further remove the noise effect by discarding most of the noise-only CIR taps. Specifically, the IMOT scheme is achieved by recovering the CIR support across the optimal "tap-to-tap" threshold derived by minimizing the MSE of each CIR tap. Moreover, the prior confidence level of the tap to be active is calculated through multi-frame statistics to further improve the performance of the IMOT scheme. Simulation results verify that the proposed AMA-IMOT channel estimation method can achieve better performance than comparison methods. INDEX TERMS Sparse channel estimation; multiple-input multiple-output (MIMO); orthogonal frequency division multiplexing (OFDM); space time block coding (STBC); multi-frame averaging; threshold.

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Section: B Related Workmentioning

confidence: 99%

“…According to the research of Zhang et al [45], a suitable choice of the average frame number is related to the Doppler spread and the operating SNR in the time-varying channel.…”

Section: B Related Workmentioning

confidence: 99%

Section: Time-domain Ls Channel Estimationmentioning

confidence: 99%

“…The estimation of d f is investigated in [45], and it is based on the fact that the autocorrelation function of the received pilot symbols is the same as that of the CIR, i.e.…”

Section: ) Estimation Of Unknow Parametersmentioning

confidence: 99%

“…, and then let that j be z. Then, the first zero crossing point 0 z of () j  can be calculated as [45]:…”

Section: ) Estimation Of Unknow Parametersmentioning

confidence: 99%

See 3 more Smart Citations

Time-Varying Sparse Channel Estimation Based on Adaptive Average and MSE Optimal Threshold in STBC MIMO-OFDM Systems

2020

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Robust and Sparse Dual Tree Complex Wavelet Transform-Based Twin Support Vector Regression for 5G InH and V2I Communications

Charrada

Samet²

2022

Wireless Pers Commun

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Twin Support Vector Regression for complex millimetric wave propagation environment

Charrada

Samet

2020

Heliyon

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In this article, an effective millimetric wave channel estimation algorithm based on Twin Support Vector Regression (TSVR) is proposed. This algorithm exploits Discrete Wavelet Transform (DWT) in order to denoise samples in learning phase and then enhance fitting performance. An indoor complex conference room environment full of furniture and electronic equipments is adopted for experiments. Through the proposed approach, channel frequency responses are directly estimated using the Orthogonal Frequency Division Multiplexing (OFDM) reference symbol pattern by solving two quadratic programming problems in order to improve generalization aptitude and computational speed. We consider in this work a Channel Impulse Response (CIR) of 60 GHz multipath transmission system generated by the "Wireless InSite" ray tracer by Remcom. The numerical experiments confirm the performance of the proposed approach compared to other conventional algorithms for several configuration scenarios with and without mobility.

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A Novel Noise Suppression Channel Estimation Method Based on Adaptive Weighted Averaging for OFDM Systems

Cited by 15 publications

References 38 publications

Time-Varying Sparse Channel Estimation Based on Adaptive Average and MSE Optimal Threshold in STBC MIMO-OFDM Systems

Time-Varying Sparse Channel Estimation Based on Adaptive Average and MSE Optimal Threshold in STBC MIMO-OFDM Systems

Robust and Sparse Dual Tree Complex Wavelet Transform-Based Twin Support Vector Regression for 5G InH and V2I Communications

Twin Support Vector Regression for complex millimetric wave propagation environment

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