Uplink Channel Estimation and Equalization in NB-IoT System

V. Savaux, Hamidou Dembélé, M. Kanj
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引用次数: 5

Abstract

This paper deals with channel estimation and equalization, as well as noise variance estimation in uplink narrowband-internet of things (NB-IoT) system. Different techniques are studied in the context of NB-IoT, such as least square (LS) and linear minimum mean square error (LMMSE) for channel estimation, and zero forcing (ZF) and MMSE for equalization. It is shown that a low-complexity application of MMSE-based methods is made possible in NB-IoT by taking advantage of the small number of subcarriers. Furthermore, a noise variance estimator is suggested based on the combination of two successive observations of pilots, assuming slowly varying channel. We also prove that the proposed estimator is efficient, and confirm by simulations that both LMMSE channel estimator and MMSE equalizer can use the estimated noise variance instead of the exact value without loss of performance.
NB-IoT系统中的上行信道估计与均衡
本文研究了窄带物联网(NB-IoT)上行系统中的信道估计和均衡以及噪声方差估计。在NB-IoT背景下研究了不同的技术,例如用于信道估计的最小二乘(LS)和线性最小均方误差(LMMSE),以及用于均衡的零强迫(ZF)和MMSE。研究表明,利用子载波数量少的优势,可以实现基于mmse的方法在NB-IoT中的低复杂度应用。此外,在假设信道缓慢变化的情况下,提出了一种基于导频两次连续观测的噪声方差估计方法。我们还证明了所提出的估计器是有效的,并通过仿真验证了LMMSE信道估计器和MMSE均衡器都可以在不损失性能的情况下使用估计的噪声方差而不是精确值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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