Channel Estimation Scheme Using Superimposed Training Sequences with Low Power

LUO Ren-ze; CHEN Ning; ZHOU Guo-Tong

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Channel Estimation Scheme Using Superimposed Training Sequences with Low Power

更新时间：2025-07-16

- Channel Estimation Scheme Using Superimposed Training Sequences with Low Power
- Acta Electronica Sinica Vol. 36, Issue 1, Pages: 177-179(2008)
- 作者机构：
  
  1. 电子科技大学中山学院,广东,中山,528402
  2. School of Electrical and Computer Engineering,Georgia Institute of Technology,GA,Atlanta,USA,30332-020
  3. 电子科技大学中山学院广东中山,528402
  4. School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGA USA,30332-020
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911
- Published：2008
- 稿件说明：
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LUO Ren-ze, CHEN Ning, ZHOU Guo-Tong. Channel Estimation Scheme Using Superimposed Training Sequences with Low Power[J]. Acta Electronica Sinica, 2008, 36(1): 177-179.
DOI：

LUO Ren-ze, CHEN Ning, ZHOU Guo-Tong. Channel Estimation Scheme Using Superimposed Training Sequences with Low Power[J]. Acta Electronica Sinica, 2008, 36(1): 177-179. DOI：

摘要

本文提出了一种利用叠加弱能量的周期训练序列进行信道估计的线性最小均方误差(LMMSEE)算法.该方法不需要信道先验信息、不占用宝贵的带宽资源、计算量比常规LS方法更低.理论分析和计算机仿真表明:在训练序列周期比信道冲击响应长度大时

在较低的信噪比下

利用LMMSEE方法估计信道性能比LS方法更佳.

Abstract

A novel superimposed periodic pilot scheme for finite-impulse response (FIR) channel estimation

the linear minimum mean square error estimator (LMMSEE)

is investigated.The advantage of the method is that it is simpler to implement without sacrificing the data rate as it needs no information on the channel statistics.Theoretical analysis and computer simulation show that the proposed method are found to exhibit better performance than that of the linear square (LS) method at lower SNR values

provided that the number of pilot tones is sufficiently greater than the channel impulse response’s length.

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