Issue |
MATEC Web of Conferences
Volume 56, 2016
2016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
|
|
---|---|---|
Article Number | 05014 | |
Number of page(s) | 4 | |
Section | Modern Communication Technology and Applications | |
DOI | https://doi.org/10.1051/matecconf/20165605014 | |
Published online | 26 April 2016 |
Channel Estimation on the (EW) RLS Algorithm Model of MIMO OFDM in Wireless Communication
Faculty of Electrical Engineering , UiTM Shah Alam, 40000, Malaysia
This paper study the channel estimation based on the exponentially weighted (EW) RLS algorithm. The advantages of the proposed estimator arise from its implementation in the time-domain, whereas fewer channel parameters are required to be estimated compared with the frequency-domain channel coefficients. In addition, the matrix inversion operation required in LS and LMMSE estimators is avoided here by recursively updating the channel estimates. Therefore, the computational complexity is highly reduced compared to frequency-domain based channel estimation. Furthermore, the proposed estimator has good tracking capability due to exploiting the time correlation between the path gains. This paper provides analysis, evaluation and computer simulations in MATLAB. The performance is evaluated in terms of the MSE of the channel estimate and BER for different Doppler frequencies (correspond to different mobility speeds) and Monte Carlo simulations are performed and the MSE and BER performance versus SNR are obtained by averaging over 10000 channel realization. For comparisons, the BER performance is also presented for perfectly known channel at the receiver. In all the simulations, perfect synchronization between the transmitter and the receiver is assumed.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.