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基于分组的正交频分复用(OFDM)系统中的符号级选择性信道估计

Symbol-Level Selective Channel Estimation in Packet-Based OFDM Systems.

作者信息

Choi Joo-Young, Mun Cheol, Yook Jong-Gwan

机构信息

Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea.

Department of Electronic Engineering, Korea National University of Transportation, Chungju 27469, Korea.

出版信息

Sensors (Basel). 2020 Feb 26;20(5):1274. doi: 10.3390/s20051274.

Abstract

Wireless access in vehicular environments to support wireless communication between vehicles has been developed to provide road safety and infotainment services. In vehicular environments where the channel changes rapidly, channel estimation is very important in improving the reliability of wireless communication. Therefore, numerous channel estimation schemes have been proposed; however, none of the schemes proposed so far can perform well over the entire signal-to-noise ratio (SNR) region. In this paper, we propose a novel channel estimation scheme that selectively uses the better scheme between two channel estimation schemes on a symbol-by-symbol basis. The results show that the proposed scheme performs symbol-by-symbol selection of the better channel estimation scheme within a packet, and thus shows excellent performance over the entire SNR region in vehicular environments in terms of the bit error rate and packet error rate.

摘要

为支持车辆间的无线通信,已开发出车辆环境中的无线接入技术,以提供道路安全和信息娱乐服务。在信道快速变化的车辆环境中,信道估计对于提高无线通信的可靠性非常重要。因此,人们提出了许多信道估计方案;然而,迄今为止提出的所有方案在整个信噪比(SNR)区域内都无法良好运行。在本文中,我们提出了一种新颖的信道估计方案,该方案在逐个符号的基础上,从两种信道估计方案中选择性地使用更好的方案。结果表明,所提出的方案在一个数据包内对更好的信道估计方案进行逐个符号的选择,因此在车辆环境中的整个SNR区域内,就误码率和分组错误率而言,都表现出优异的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f2e/7085606/e4835fac6ead/sensors-20-01274-g001.jpg

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