American Journal of Applied Sciences

A Novel Channel Estimation Technique for Complexity Reduction of Least Minimum Mean Square Error

Hany Mohamed El-Ansary, Hussein Ghouz, Ashraf Mamdouh Aziz and Gamal Mabrouk

DOI : 10.3844/ajassp.2013.1181.1190

American Journal of Applied Sciences

Volume 10, Issue 10

Pages 1181-1190


Channel estimation technique is to predict the frequency response of the radio channel using pilot signal. Channel estimation technique is important part of LTE receiver design. Such technique is used to recover the transmitted signal correctly and to know how the channel conditions are changed over frequency and time. Each channel estimator has a specified complexity computed according to its mathematical model. Complexity Reduction of any channel estimator is very important to achieve high performance. This paper studied in details the performance enhancement of LMMSE channel estimation technique in the downlink of LTE system. The proposed algorithm is based on Roza Zheng channel model and the matrix transpose rather than matrix inverse. This dramatically reduces the complexity of LMMSE. In adition, the complexity of the proposed algorithm is invariant with the number of multipath components in case of fast fading channels. Moreover, the received signal quality has been improved as compared to the LS. The processing time of the proposed algorithm is reduced by using new criteria of auto correlation. The performance of the proposed algorithm has been evaluated using the mean squared error as the performance metric. Simulation results showed that the MSE is reduced by 89.5% for LS and by 38.7% for LMMSE. Finally, the bit error rate has been enhanced using the proposed algorithm.


© 2013 Hany Mohamed El-Ansary, Hussein Ghouz, Ashraf Mamdouh Aziz and Gamal Mabrouk. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.