[1]束锋,陈明,程时昕,等.MIMO-OFDM系统低复杂度时频ML信道估计器[J].东南大学学报(自然科学版),2006,36(5):700-704.[doi:10.3969/j.issn.1001-0505.2006.05.004]
　Shu Feng,Chen Ming,Cheng Shixin,et al.Low-complexity time-frequency channel estimator ML for MIMO-OFDM system[J].Journal of Southeast University (Natural Science Edition),2006,36(5):700-704.[doi:10.3969/j.issn.1001-0505.2006.05.004]
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MIMO-OFDM系统低复杂度时频ML信道估计器()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
36
期数:
2006年第5期
页码:
700-704
栏目:
信息与通信工程
出版日期:
2006-09-20

文章信息/Info

Title:
Low-complexity time-frequency channel estimator ML for MIMO-OFDM system
作者:
束锋1; 2;  陈明2;  程时昕2;  孙锦涛1
1 南京理工大学电子工程与光电技术学院, 南京 210094; 2 东南大学移动通信国家重点实验室, 南京 210096
Author(s):
Shu Feng1; 2;  Chen Ming2;  Cheng Shixin2;  Sun Jintao1
1 School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China
2 National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
关键词:
多输入多输出技术;  正交频分复用;  重叠;  最大似然;  信道估计
Keywords:
multiple input-multiple output;  orthogonal frequency division multiplexing;  overlapped;  maximum likelihood;  channel estimator
分类号:
TN929.5
DOI:
10.3969/j.issn.1001-0505.2006.05.004
摘要:
通过联合优化训练符号设计和ML准则, 构造了一种基于重叠训练图样的拥有低PAPR的时频信道估计器ML-A+LI.通过理论分析获得: 当训练符号矩阵等于归一化Hadamard矩阵且在子载波上等间距的摆放时,ML-A+LI估计器实现等同于正交的ML信道估计器ML-B+LI最优的MSE 性能和低复杂度.在MIMO移动信道仿真表明:ML-A+LI和ML-B+LI的BER性能介于LMMSE+LMMSE和LI+LI之间, 更接近于LMMSE+LMMSE; 当信道变化较慢时, ML-A+LI和ML-B+LI具有相同的BER 性能, 当信道变化较快时,ML-A+LI比ML-B+LI提供了更优的BER性能.
Abstract:
A low-complexity time-frequency channel estimator maximum likelihood(ML)-A+LI(linear interpolation)with overlapped training pattern(TP)and low peak-to-average power ratio(PAPR)is constructed by virtue of both optimal training pattern design and ML rule. It can achieve the optimal mean square error(MSE)performance and low complexity as ML-B+LI using orthogonal TP under the conditions that training symbol vectors are equispaced placement over subcarriers and training symbol matrix is a normalized Hadamard matrix. From simulation and analysis in multiple input-multiple output(MIMO)mobile channel, the following facts are found: ① the bit error ration(BER)performance of ML-A+LI and ML-B+LI is worse than that of LMMSE+LMMSE(linear minimum mean square error)and better than that of LI+LI, but is more close to that of LMMSE+LMMSE; ② ML-A+LI achieves the same performance as ML-B+LI for slow car speed whereas the former performs better than the latter for fast car speed.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学重大基金资助项目(60496311)、东南大学移动通信国家重点实验室开放课题资助项目(200609).
作者简介: 束锋(1973—), 男,博士, 副教授, fengshu@seu.edu.cn.
更新日期/Last Update: 2006-09-20