Channel Estimation for OFDM Systems Based on RLS and Superimposed Training Sequences
The recursive least squares (RLS) algorithm and the superimposed training sequences are applied to the orthogonal frequency division multiplexing (OFDM) systems to estimate channel state information (CSI). In order to reduce the interference caused by the unknown information data that is added with the superimposed training sequences, we present the following method: first, the information data are detected using the CSI of the previous one block, and then subtracted them from the current received signals. Second, the remainder signals mainly including the training sequence are used to estimate CSI. For decreasing the computation complexity, we use the same training sequence in all OFDM blocks. The computation complexity and the mean square error (MSE) performance of our proposed RLS method are compared with the original RLS method.
superimposed training sequence RLS channel estimation
Jinjing Zhan Jun Wang Shouyin Liu Jong-Wha Chong
The Dept. of Electronic & Information Engineering Huazhong Normal University Wuhan 430079, China The College of Information & Communications Hanyang University Seoul 133-791, Korea
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）