Low Complexity Two-Dimensional Channel Estimation Algorithm for Broadband SC-FDE System

Qifeng Zou; Xuezhi Tan; Mei Liu; Yonggang Chi

doi:10.3969/j.issn.1000-0801.2014.08.015

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Low Complexity Two-Dimensional Channel Estimation Algorithm for Broadband SC-FDE System

research and development | 更新时间：2024-06-05

- Low Complexity Two-Dimensional Channel Estimation Algorithm for Broadband SC-FDE System
- Telecommunications Science Vol. 30, Issue 8, Pages: 93-98(2014)
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- DOI：10.3969/j.issn.1000-0801.2014.08.015
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- Published Online：2014-08，
  
  Published：15 August 2014
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Qifeng Zou, Xuezhi Tan, Mei Liu, et al. Low Complexity Two-Dimensional Channel Estimation Algorithm for Broadband SC-FDE System[J]. Telecommunications science, 2014, 30(8): 93-98.
DOI：

Qifeng Zou, Xuezhi Tan, Mei Liu, et al. Low Complexity Two-Dimensional Channel Estimation Algorithm for Broadband SC-FDE System[J]. Telecommunications science, 2014, 30(8): 93-98. DOI： 10.3969/j.issn.1000-0801.2014.08.015.

摘要

单载波频域均衡系统因具有峰均比低、适用于高速率传输的优势，具有广泛的应用前景，同时对其信道估计性能也提出了一定的要求。针对传统一维MMSE估计算法性能较差，而二维算法运算复杂度又较高的问题，依据信道的时频分离特性提出了一种低复杂度二维MMSE信道估计算法。将二维估计转化为两个一维估计，再通过改进的SVD 算法减小一维估计的复杂度，并通过在帧结构插入特殊字（UW）序列作为循环前缀来减小系统开销，进行噪声方差估计。理论分析及仿真结果表明，本文算法比传统的LS及MMSE信道估计算法在未编码系统及编码系统中的性能都更好，且运算复杂度比传统一维MMSE算法更低。

Abstract

Single carrier frequency domain equalization（SC-FDE）is widely recognized as an very promising technique for its lower peak-to-average power ratio

but it also needs more accurate channel estimation method. A low complexity two-dimensional MMSE channel estimation algorithm based on time-frequency domain separation feature of channel was proposed in order to improve estimation performance and predigest the complexity. The two-dimensional MMSE estimation can be simplified as two one-dimensional MMSE and the SVD algorithm was used to reduce the complexity of one-dimensional estimation. The UW as the cyclic prefix could reduce the overhead of system. Noise variance was also estimated at the UW. The simulation results show that the proposed algorithm has better performance than the conventional LS algorithm and MMSE algorithm. The complexity of the proposed algorithm was also lower than the conventional one-dimensional MMSE method.

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references

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