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Pilot-Based Time Domain SNR Estimation for Broadcasting OFDM Systems

机译:广播OFDM系统中基于导频的时域SNR估计

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The estimation of signal-to-noise ratio (SNR) is a major issue in wireless orthogonal frequency-division multiplexing (OFDM) system. In OFDM system, each frame starts with a preamble symbol that facilitates the SNR estimation. However, the performance of preamble-based SNR estimation schemes worsens in the fast-changing environment where channel changes symbol to symbol. Accordingly, in this paper, we propose a novel pilot-based SNR estimation scheme that optimally exploits the pilot subcarriers that are inserted in each data symbol of the OFDM frame. The proposed scheme computes the circular correlation between the received signal and the comb-type pilot sequence to obtain the SNR. The simulation results are compared with the conventional preamble-based Zadoff-Chu sequence SNR estimator. The results indicate that the proposed scheme generates near-ideal accuracy; especially in low SNR regimes, in terms of the normalized mean square error (NMSE). Moreover, this scheme offers a significant saving of computation over a conventional time domain SNR estimator.
机译:信噪比(SNR)的估计是无线正交频分复用(OFDM)系统中的主要问题。在OFDM系统中,每个帧都以一个前导符号开始,该符号有利于SNR估计。但是,在信道随符号变化的快速变化的环境中,基于前导的SNR估计方案的性能会变差。因此,在本文中,我们提出了一种新颖的基于导频的SNR估计方案,该方案可以最佳地利用插入OFDM帧的每个数据符号中的导频子载波。所提出的方案计算接收信号与梳型导频序列之间的循环相关性以获得SNR。仿真结果与传统的基于前同步码的Zadoff-Chu序列SNR估计器进行了比较。结果表明,该方案产生了近乎理想的精度。特别是在低SNR方案中,就归一化均方误差(NMSE)而言。此外,与传统的时域SNR估计器相比,该方案可节省大量计算时间。

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