Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA

Yong LIAO; Zhirong CAI

doi:10.11959/j.issn.1000-436x.2021081

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Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA

Papers | 更新时间：2024-06-05

- Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA
- Journal on Communications Vol. 42, Issue 4, Pages: 177-184(2021)
- 作者机构：
  
  重庆大学微电子与通信工程学院，重庆 400044
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61501066);The Natural Science Foundation of Chongq-ing(cstc2019jcyj-msxmX0017)
- DOI：10.11959/j.issn.1000-436x.2021081
  CLC： TN911.72
- Online First：2021-04，
  
  Published：25 April 2021
- 稿件说明：
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Yong LIAO, Zhirong CAI. Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA[J]. Journal on Communications, 2021, 42(4): 177-184.
DOI：

Yong LIAO, Zhirong CAI. Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA[J]. Journal on Communications, 2021, 42(4): 177-184. DOI： 10.11959/j.issn.1000-436x.2021081.

摘要

为了进一步提升车联万物（V2X）的通信性能，首先根据信道冲激响应的稀疏性建立了适用于高速移动场景的基扩展模型（BEM）；其次，证明了BEM系数具有稀疏性，将信道估计问题转化为稀疏信号重构问题，进而提出基于 BEM 的改进正则化正交匹配追踪（iROMP）迭代稀疏信道估计算法（简称为 BEM-iROMP 算法）。所提算法通过iROMP获取BEM系数，利用反馈结果不断迭代以达到最优信道估计。仿真结果表明，与最小二乘法、线性最小均方误差和BEM-LS信道估计算法相比，所提算法能够有效提高V2X快时变信道下单载波频分多址系统的归一化均方误差和误码率性能。

Abstract

In order to further improve the vehicle-to-everything (V2X) communication performance of the Internet of vehicles

a basis expansion model (BEM) was adopted and suitable for high-speed mobile scenarios to transform the channel estimation into a sparse signal reconstruction.Furthermore

it was proved that the BEM coefficients were sparse

and an improved regularized orthogonal matching pursuit (iROMP) channel estimation algorithm based on BEM (BEM-iROMP) was proposed.BEM coefficients were acquired by the iROMP

and finally the feedback results were iterated to achieve the optimal channel estimation.Simulation results show that in comparison with the least square (LS)

linear minimum mean squared error (LMMSE)

and BEM-LS channel estimation algorithms

the proposed algorithm can effectively improve the normalized mean square error (NMSE) and bit error rate (BER) performance.

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Keywords

references

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