scholarly journals Improving MIMO-OFDM decision-directed channel estimation by utilizing error-correcting codes

2009 ◽  
Vol 7 ◽  
pp. 83-88
Author(s):  
P. Beinschob ◽  
M. Lieberei ◽  
U. Zölzer
Keyword(s):  
Channel Estimation ◽  
Turbo Codes ◽  
Adaptive Filters ◽  
Multiple Input Multiple Output ◽  
Error Correcting Codes ◽  
Mimo Channel ◽  
Time Frequency ◽  
Coding Schemes ◽  
Channel Estimate ◽  
Input Multiple Output

Abstract. In this paper a decision-directed Multiple-Input Multiple-Output (MIMO) channel tracking algorithm is enhanced to raise the channel estimate accuracy. While DDCE is prone to error propagation the enhancement employs channel decoding in the tracking process. Therefore, a quantized block of symbols is checked on consistency via the channel decoder, possibly corrected and then used. This yields a more robust tracking of the channel in terms of bit error rate and improves the channel estimate under certain conditions. Equalization is performed to prove the feasibility of the obtained channel estimate. Therefore a combined signal consisting of data and pilot symbols is sent. Adaptive filters are applied to exploit correlations in time, frequency and spatial domain. By using good error-correcting coding schemes like Turbo Codes or Low Density Parity Check (LDPC) codes, adequate channel estimates can be acquired even at low signal to noise ratios (SNR). The proposed algorithm among two others is applied for channel estimation and equalization and results are compared.

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.

Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System

2015 ◽  
Vol 24 (04) ◽  
pp. 1550059 ◽  
Author(s):  
Gajanan R. Patil ◽  
Vishwanath K. Kokate
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Channel Estimate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
The Cost ◽  
Joint Channel

This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach gives better performance over training-based channel estimation (TBCE) and OPML SBCE methods but at the cost of higher computational complexity.

SUPERIMPOSED TRAINING-BASED CHANNEL ESTIMATION FOR MIMO-MB-OFDM UWB SYSTEMS

2008 ◽  
Vol 17 (05) ◽  
pp. 865-870 ◽  
Author(s):  
QINGHAI YANG ◽  
HUAMIN ZHU ◽  
KYUNG SUP KWAK
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Ultra Wideband ◽  
Superimposed Training ◽  
Square Channel ◽  
Channel Estimate ◽  
Input Multiple Output ◽  
Estimation Scheme

A novel channel estimation scheme based on superimposed training is proposed for multiple-input multiple-output multi-band orthogonal frequency division multiplexing ultra-wideband systems. The optimal training symbols are derived with respect to the least-square channel estimate mean square error. Simulation shows that the proposed scheme benefits much higher effective data throughput over the conventional method.

PILOT-AIDED MULTIUSER CHANNEL ESTIMATION AND TRACKING IN MIMO-OFDM SYSTEMS

2007 ◽  
Vol 16 (03) ◽  
pp. 319-335 ◽  
Author(s):  
QINGHAI YANG ◽  
KYUNG SUP KWAK
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Estimation Methods ◽  
Ofdm Systems ◽  
Estimation Algorithms ◽  
Channel Estimate ◽  
Multiuser Channel ◽  
Input Multiple Output

This paper addresses the pilot-aided multiuser least square (LS) channel estimation for the uplink of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The systems under consideration allow all users use all available subcarriers independently and thus involve multiuser interference in the frequency domain. Direct application of the known pilot-aided single-user channel estimation methods to these systems is prohibited, requiring much more new investigations. The decentralized and centralized channel estimation algorithms are developed according to different multiuser scenarios. Optimal multiuser pilots are proposed, especially for centralized estimation methods with respect to the mean square error (MSE) of LS channel estimate. In addition, channel tracking algorithms are represented in terms of individual user's channels.

scholarly journals Effect of Antenna Mutual Coupling on MIMO Channel Estimation and Capacity

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Xia Liu ◽  
Marek E. Bialkowski
Keyword(s):  
Channel Estimation ◽  
Mutual Coupling ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Channel State ◽  
Estimation Errors ◽  
Channel Estimation Errors ◽  
Perfect Channel State Information ◽  
Multiple Input ◽  
Input Multiple Output

This paper describes investigations into the antenna mutual coupling (MC) effect on channel estimation and capacity of a multiple-input multiple-output (MIMO) wireless communication system. The presented investigations close the gap existing in the previous works which assessed the effect of mutual coupling on MIMO capacity under the assumption of availability of perfect channel state information (CSI) at the receiver. The new approach assumes that the perfect CSI is not available due to channel estimation errors. The investigations are carried out for different spacing between array antenna elements producing a varying effect of mutual coupling on the channel estimation and the resulting MIMO channel capacity.

scholarly journals Channel Estimation Performance Analysis of FBMC/OQAM Systems with Bayesian Approach for 5G-Enabled IoT Applications

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Han Wang ◽  
Wencai Du ◽  
Xianpeng Wang ◽  
Guicai Yu ◽  
Lingwei Xu
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Communication Systems ◽  
Channel Model ◽  
Matching Pursuit ◽  
Multiple Input Multiple Output ◽  
Filter Bank Multicarrier ◽  
Channel Parameter ◽  
Input Multiple Output ◽  
Estimation Scheme

A filter bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) (FBMC/OQAM) is considered to be one of the physical layer technologies in future communication systems, and it is also a wireless transmission technology that supports the applications of Internet of Things (IoT). However, efficient channel parameter estimation is one of the difficulties in realization of highly available FBMC systems. In this paper, the Bayesian compressive sensing (BCS) channel estimation approach for FBMC/OQAM systems is investigated and the performance in a multiple-input multiple-output (MIMO) scenario is also analyzed. An iterative fast Bayesian matching pursuit algorithm is proposed for high channel estimation. Bayesian channel estimation is first presented by exploring the prior statistical information of a sparse channel model. It is indicated that the BCS channel estimation scheme can effectively estimate the channel impulse response. Then, a modified FBMP algorithm is proposed by optimizing the iterative termination conditions. The simulation results indicate that the proposed method provides better mean square error (MSE) and bit error rate (BER) performance than conventional compressive sensing methods.

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