scholarly journals Precoding Aided Data Correlation Scheme for Channel Estimation Technique in MIMO-OFDM System

2021 ◽  
Vol 16 ◽  
pp. 146-154
Author(s):  
Sidramayya S. Matad ◽  
Ramesha K.
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Multiple Input Multiple Output ◽  
Blind Channel Estimation ◽  
Mean Square ◽  
Estimation Technique ◽  
Blind Channel ◽  
Mimo Ofdm

Channel estimation is considered as an important phase in Multiple Input Multiple Output – Orthogonal Frequency Division Multiplexing (MIMO-OFDM) networks which can enhances the performance significantly. Channel estimation widely classified as pilot based, blind and semi-blind channel estimation. The pilot-based channel estimation decreases the data transmission rate and spectral efficiency. To overcome these issues of existing schemes, we present a novel blind channel estimation technique. According to proposed scheme, we transmit the data in a block-wise manner. The proposed scheme uses precoding technique to establish the correlation between these blocks. Further, we use channel correlation to solve the diagonal uncertainty of correlation matrix which helps to improve the system performance. We present a comparative analysis study which shows that proposed approach can achieve better performance in terms of Normalized Mean Square Error (NMSE) and Mean Square Error (MSE) when compared with existing techniques.

scholarly journals A Comprehensive Review on Channel Estimation in OFDM System

2019 ◽  
Vol 5 (3) ◽  
pp. 6 ◽  
Author(s):  
Neha Dubey ◽  
Ankit Pandit
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Minimum Mean Square Error ◽  
Estimation Method ◽  
Least Square ◽  
Estimation Methods ◽  
Mean Square ◽  
Mimo Ofdm

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.

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.

scholarly journals Joint Adaptive Blind Channel Estimation and Data Detection for MIMO-OFDM Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ruo-Nan Yang ◽  
Wei-Tao Zhang ◽  
Shun-Tian Lou
Keyword(s):  
Channel Estimation ◽  
Cost Function ◽  
Least Squares ◽  
Orthogonal Frequency Division Multiplexing ◽  
Blind Channel Estimation ◽  
Recursive Least Squares ◽  
Ofdm Systems ◽  
Blind Channel ◽  
Mimo Ofdm ◽  
The Cost

In order to track a changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is a priority to estimate channel impulse response adaptively. In this paper, we propose an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weigh 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 a third-order tensor, which consists of the weighted OFDM data symbols. By preserving the Khatri-Rao product, we used a recursive least squares solution to update the estimated subspace at each time instant, then the channel parameters can be estimated adaptively, and the algorithm achieves superior convergence performance. Simulation results validate the effectiveness of the proposed algorithm.

scholarly journals Channel Estimation in MIMO-OFDM System

2014 ◽  
Vol 14 (2) ◽  
pp. 97-102
Author(s):  
SR Aryal ◽  
H Dhungana
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multipath Fading ◽  
Spatial Multiplexing ◽  
Diversity Gain ◽  
Estimation Methods ◽  
Mean Square ◽  
Ofdm System ◽  
Mimo Ofdm

There are no limit of human desire, so day by day we need much higher data speed to facilitate our need but every physical resource like frequency band, transmit signal strength are finite. Within the given limited resource, higher data speed is accomplished by new proficiency called Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM) system. MIMO-OFDM fulfills the high data rate requirement through spatial multiplexing gain and improved link reliability due to antenna diversity gain. With this technique, both interference reduction and maximum diversity gain are achieved by increasing number of antennae on either side. Received signal in MIMO-OFDM system is usually distorted by multipath fading. In order to recover the transmitted signal correctly, channel effect must be estimated and repaired at receiver. In this paper the performance evaluating parameter mean square error and symbol error rate of least square error, minimum mean square error and DFT based channel estimation methods are estimated and appropriate solution is recommended. Furthermore, comparison among their characteristics is simulated in MATLAB and useful conclusion is delineated. DOI: http://dx.doi.org/10.3126/njst.v14i2.10421   Nepal Journal of Science and Technology Vol. 14, No. 2 (2013) 97-102

Optimised periodic precoder-based blind channel estimation for MIMO-OFDM systems

2017 ◽  
Vol 6 (3) ◽  
pp. 347-363
Author(s):  
Bhasker Gupta ◽  
Shivani Gupta ◽  
Ashutosh Kumar Singh ◽  
Hem Dutt Joshi
Keyword(s):  
Channel Estimation ◽  
Blind Channel Estimation ◽  
Ofdm Systems ◽  
Blind Channel ◽  
Mimo Ofdm

A New Method for MIMO-OFDM Channel Estimation Based on Discrete Wavelet Transform

2012 ◽  
Vol 182-183 ◽  
pp. 2066-2070
Author(s):  
Hui Shi ◽  
Ren Wang Song ◽  
Gang Fei Wang
Keyword(s):  
Wavelet Transform ◽  
Channel Estimation ◽  
Discrete Wavelet Transform ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Discrete Wavelet ◽  
Input Multiple Output ◽  
Estimation Scheme ◽  
Mimo Ofdm

This paper puts forward a suitable channel estimation scheme for multiple input multiple output and orthogonal frequency division multiplexing system (MIMO-OFDM) based on discrete wavelet transform. According to the least-squares standard (LS), this plan uses pilot to estimate the unit impulse response of MIMO channel firstly, then does wavelet denoising in changing domain, in order to reduce the frequency spectrum leakage and improve the estimation precision. At the same time, this method does not need to know channel information in advance, and can follow up the changes of channel on time with good error rate performance.

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