@inproceedings{44266191f29f49e1b4971b4bc017d8b5,
title = "A Channel Estimation Method Based on the Improved LMS Algorithm for MIMO-OFDM Systems",
abstract = "The least mean square (LMS) algorithm is a kind of typical adaptive filter algorithms. The algorithm of channel estimation algorithm based on LMS is no need to know the characteristics of channel and noise statistics, which make full use of channel correlation between front and back to reduce the influence of noise on channel estimation performance. In this paper, the LMS algorithm has been improved under the MIMO-OFDM systems. Then, a revised method for variable step size has been put forward, which accelerates the rate of convergence to improve channel estimation performance preferably. The simulation results show that the algorithm proposed in this paper not only has the fastest convergence compared with LMS and NLMS algorithm, but also has a better channel estimation(CE) performance than other estimation algorithms.",
keywords = "MIMO-OFDM, NLMS, channel estimation, the least mean square algorithm, variable step size",
author = "Zhenfeng Zhang and Limin Xiao and Xin Su and Jie Zeng and Xibin Xu",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 12th International Symposium on Medical Information and Communication Technology, ISMICT 2018 ; Conference date: 26-03-2018 Through 28-03-2018",
year = "2018",
month = dec,
day = "11",
doi = "10.1109/ISMICT.2018.8573728",
language = "English",
series = "International Symposium on Medical Information and Communication Technology, ISMICT",
publisher = "IEEE Computer Society",
booktitle = "12th International Symposium on Medical Information and Communication Technology, ISMICT 2018",
address = "United States",
}