Iterative channel estimation using superimposed training and weighted-least-square method

被引：0

作者：

Zhang, Hua ^{[1
]}

Zhu, Jinkang ^{[1
]}

机构：

[1] Department of Electronics Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China

来源：

Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2008年 / 36卷 / 04期

关键词：

Bit error rate - Mean square error - Signal to noise ratio;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

An iterative estimation algorithm for FIR time-invariant or slowly time-varying channels is proposed by superimposed training method, in which the periodical deterministic sequence was arithmetically added to the data sequence and the first-order and the second-order statistics of the received sequence were used. The estimate error of the proposed algorithm is smaller than that of the first order statistics method, and the self-correlation's positive definite property of the received random sequence makes the new estimate algorithm robust. The simulation results show that the iteration converges rapidly when applying special initial channel values, and the MSE performance of the proposed algorithm is better than that of the first order method. Meanwhile the BER performance under the situation of constant transmit power is given.

引用

页码：13 / 16