计算机工程

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基于数据相关叠加训练序列的载波频偏与信道联合估计

凌琪琪,罗志年   

  1. (湖南大学 信息科学与工程学院,长沙 410082)
  • 收稿日期:2016-07-28 出版日期:2017-09-15 发布日期:2017-09-15
  • 作者简介:凌琪琪(1991—),男,硕士,主研方向为无线通信;罗志年,副教授、博士。
  • 基金项目:
    国家自然科学基金(61371115)。

Joint Estimation of Carrier Frequency Offset and Channel Based on Data Dependent Superimposed Training Sequence

LING Qiqi,LUO Zhinian   

  1. (College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082,China)
  • Received:2016-07-28 Online:2017-09-15 Published:2017-09-15

摘要:

针对正交频分复用(OFDM)系统对载波频偏敏感的问题,提出一种载波频偏与信道的联合估计算法。通过相邻2个OFDM符号间的相位差进行频偏估计,使用迭代算法提高估计精度。利用数据相关叠加训练序列在频域的特性,对2个连续的OFDM符号进行信道估计,并且采用基扩展模型拟合信道提高估计性能。仿真结果表明,该算法可在不增加系统复杂度及带宽的情况下实现载波频偏及信道的稳健估计。

关键词: 正交频分复用, 数据相关叠加训练序列, 频偏估计, 基扩展模型, 信道估计

Abstract: Focusing on the sensitivity to carrier frequency offset in the Orthogonal Frequency Division Multiplexing(OFDM) system,a joint estimation algorithm of carrier frequency offset and channel is proposed in this paper.The frequency offset is estimated through the phase difference between two adjacent OFDM symbols,and the accuracy of estimation is improved by an iteration algorithm.Meanwhile,referring the characteristics of Data Dependent Superimposed Training(DDST) at the frequncy domain are used to estimate two consecutive OFDM channels,and the Basis Expansion Model(BEM) fitting channel is employed to improve the estimation performance.The simulation results show that the proposed algorithm can robustly estimate the carrier frequency offset and channel without increasing system complexity and sacrificing the bandwidth.

Key words: Orthogonal Frequency Division Multiplexing(OFDM), Data Dependent Superimposed Training(DDST) sequence, frequency offset estimation, Basis Expansion Model(BEM), channel estimation

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