Structured channel estimation methods for cooperative underwater communication

In wireless communication, orthogonal frequency division multiplexing (OFDM) plays a major role because of its high transmission rate. Channel estimation and tracking have many different techniques available in OFDM systems. Among them, the most important techniques are least square (LS) and minimum mean square error (MMSE). In least square channel estimation method, the process is simple but the major drawback is it has very high mean square error. Whereas, the performance of MMSE is superior to LS in low SNR, its main problem is it has high computational complexity. If the error is reduced to a very low value, then an exact signal will be received. In this paper an extensive review on different channel estimation methods used in MIMO-OFDM like pilot based, least square (LS) and minimum mean square error method (MMSE) and least minimum mean square error (LMMSE) methods and also other channel estimation methods used in MIMO-OFDM are discussed.

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Comparison of two channel estimation methods

Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005. ◽

10.1109/wcnm.2005.1544096 ◽

2005 ◽

Author(s):

Qingrong Zhang ◽

Daoben Li

Keyword(s):

Channel Estimation ◽

Estimation Methods

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Research of the Channel Estimation in Wireless Communication Systems

ITM Web of Conferences ◽

10.1051/itmconf/20192501002 ◽

2019 ◽

Vol 25 ◽

pp. 01002 ◽

Cited By ~ 1

Author(s):

Lili Zhao ◽

Peng Zhang ◽

Qicai Dong ◽

Xiangyang Huang ◽

Jianhua Zhao ◽

...

Keyword(s):

Wireless Communication ◽

Channel Estimation ◽

Communication Technology ◽

Communication Systems ◽

Communication Channel ◽

Data Transfer ◽

Estimation Methods ◽

Wireless Communication Systems ◽

Data Transfer Rate

Wireless communication technology has been developed rapidly after entering the 21st century. Data transfer rate increased significantly as well as the bandwidth became wider and wider from 2G to 4G in wireless communication systems. Channel estimation is an import part of any communication systems; its accuracy determines the quality of the whole communication. Channel estimation methods of typical wireless communication systems such as UWB, 2G and 3G have been researched.

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Projection wavelet weighted twin support vector regression for OFDM system channel estimation

Artificial Intelligence Review ◽

10.1007/s10462-020-09853-2 ◽

2020 ◽

Author(s):

Lidong Wang ◽

Yimei Ma ◽

Xudong Chang ◽

Chuang Gao ◽

Qiang Qu ◽

...

Keyword(s):

Channel Estimation ◽

Support Vector Regression ◽

Orthogonal Frequency Division Multiplexing ◽

Channel Model ◽

Wireless Channel ◽

Estimation Methods ◽

Support Vector ◽

Ofdm System ◽

Twin Support Vector Regression ◽

Empirical Risk

Abstract In this paper, an efficient projection wavelet weighted twin support vector regression (PWWTSVR) based orthogonal frequency division multiplexing system (OFDM) system channel estimation algorithm is proposed. Most Channel estimation algorithms for OFDM systems are based on the linear assumption of channel model. In the proposed algorithm, the OFDM system channel is consumed to be nonlinear and fading in both time and frequency domains. The PWWTSVR utilizes pilot signals to estimate response of nonlinear wireless channel, which is the main work area of SVR. Projection axis in optimal objective function of PWWRSVR is sought to minimize the variance of the projected points due to the utilization of a priori information of training data. Different from traditional support vector regression algorithm, training samples in different positions in the proposed PWWTSVR model are given different penalty weights determined by the wavelet transform. The weights are applied to both the quadratic empirical risk term and the first-degree empirical risk term to reduce the influence of outliers. The final regressor can avoid the overfitting problem to a certain extent and yield great generalization ability for channel estimation. The results of numerical experiments show that the propose algorithm has better performance compared to the conventional pilot-aided channel estimation methods.

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

Symmetry ◽

10.3390/sym11080997 ◽

2019 ◽

Vol 11 (8) ◽

pp. 997 ◽

Cited By ~ 5

Author(s):

Zhang ◽

Zhou ◽

Wang

Keyword(s):

Fourier Transform ◽

Channel Estimation ◽

Fast Fourier Transform ◽

Orthogonal Frequency Division Multiplexing ◽

Noise Suppression ◽

Estimation Method ◽

Weighted Averaging ◽

Doppler Spread ◽

Estimation Methods ◽

Ofdm Systems

Orthogonal frequency division multiplexing (OFDM) systems have inherent symmetric properties, such as coding and decoding, constellation mapping and demapping, inverse fast Fourier transform (IFFT) and fast Fourier transform (FFT) operations corresponding to multi-carrier modulation and demodulation, and channel estimation is a necessary module to resist channel fading in the OFDM system. However, the noise in the channel will significantly affect the accuracy of channel estimation, which further affects the recovery quality of the final received signals. Therefore, this paper proposes an efficient noise suppression channel estimation method for OFDM systems based on adaptive weighted averaging. The basic idea of the proposed method is averaging the last few channel coefficients obtained from coarse estimation to suppress the noise effect, while the average frame number is adaptively adjusted by combining Doppler spread and signal-to-noise ratio (SNR) information. Meanwhile, to better combat the negative effect brought by Doppler spread and inter-carrier interference (ICI), the proposed method introduces a weighting factor to correct the weighted value of each frame in the averaging process. Simulation results show that the proposed channel estimation method is effective and provides better performance compared with other conventional channel estimation methods.

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