OFDM稀疏信道估计中的能量泄漏:OMP的缺点和图像去模糊的应用

IF 7.5 2区 计算机科学 Q1 TELECOMMUNICATIONS
Gang Qiao , Xizhu Qiang , Lei Wan , Hanbo Jia
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引用次数: 0

摘要

在本文中,为了减少正交频分复用(OFDM)系统稀疏信道估计中离散化表示引起的能量泄漏,我们从线性拟合理论的角度系统地分析了每条路径重建中具有离散延迟的原子的最佳位置。然后,我们研究了非理想内积函数对最广泛使用的信道估计方法之一--正交匹配追求(OMP)--迭代的不利影响。研究表明,在 OMP 中,每条路径所选原子之间的距离可能大于采样间隔,这使得基于 OMP 的方法无法获得更好的性能。为克服这一缺点,提出了基于图像去模糊的信道估计方法,将信道估计问题类比为一维图像去模糊,以改善传统 OMP 补偿距离过大的问题。数值模拟和海试数据解码结果验证了所提方法的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy leakage in OFDM sparse channel estimation: The drawback of OMP and the application of image deblurring
In this paper, in order to reduce the energy leakage caused by the discretized representation in sparse channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems, we systematically have analyzed the optimal locations of atoms with discrete delays for each path reconstruction from the perspective of linear fitting theory. Then, we have investigated the adverse effects of the non-ideal inner product function on the iteration in one of the most widely used channel estimation method, Orthogonal Matching Pursuit (OMP). The study shows that the distance between the selected atoms for each path in OMP can be larger than the sampling interval, which prevents OMP-based methods from achieving better performance. To overcome this drawback, the image deblurring-based channel estimation method, in which the channel estimation problem is analogized to one-dimensional image deblurring, was proposed to improve the large compensation distance of traditional OMP. The advantage of the proposed method was validated by the results of numerical simulation and sea trial data decoding.
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来源期刊
Digital Communications and Networks
Digital Communications and Networks Computer Science-Hardware and Architecture
CiteScore
12.80
自引率
5.10%
发文量
915
审稿时长
30 weeks
期刊介绍: Digital Communications and Networks is a prestigious journal that emphasizes on communication systems and networks. We publish only top-notch original articles and authoritative reviews, which undergo rigorous peer-review. We are proud to announce that all our articles are fully Open Access and can be accessed on ScienceDirect. Our journal is recognized and indexed by eminent databases such as the Science Citation Index Expanded (SCIE) and Scopus. In addition to regular articles, we may also consider exceptional conference papers that have been significantly expanded. Furthermore, we periodically release special issues that focus on specific aspects of the field. In conclusion, Digital Communications and Networks is a leading journal that guarantees exceptional quality and accessibility for researchers and scholars in the field of communication systems and networks.
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