OFDM系统中最大似然频偏估计方法的比较

H. Nezamfar, M. Kahaei
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引用次数: 2

摘要

最大似然估计发射机和接收机之间的频偏是OFDM系统中估计载波频偏的主要技术。本文给出了OFDM系统中机器学习检测问题的一般公式,并描述了如何将不同的机器学习技术视为特殊情况。此外,在统一的仿真框架下,比较了新提出的主要机器学习技术在AWGN存在下的估计范围和复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comparison of Maximum Likelihood frequency offset estimation methods for OFDM systems
Maximum likelihood (ML) estimation of the frequency offset between the transmitter and the receiver from known transmitted preambles is the dominant technique for the estimation of carrier frequency offset (CFO) in OFDM systems. A general formulation of ML detection problem for OFDM systems is provided in this paper and it is described how different ML techniques can be treated as special cases. In addition major newly proposed ML techniques are compared in a unified simulation framework in the presence of AWGN and their performance in terms of estimation range, and their complexity are compared.
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