声学OFDM系统中信道时变效应的抑制研究

A. Tadayon, Munish Taya, M. Stojanovic
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引用次数: 0

摘要

OFDM系统面临着移动声学信道的时变的挑战,其中多普勒效应可能足够高,以至于接收到的信号经历不可忽略的剩余频率偏移,以及信道时变,这会导致载波间干扰(ICI)。为了减轻这些影响,我们引入了一种高效且计算易于管理的两阶段算法,该算法可以抵消移动声学信道的频率偏移和时间选择性。在第一阶段,使用基于差分相干检测的实用方法补偿频率偏移,该方法使接收机的复杂性保持在最低水平,并且只需要很小的导频开销。在第二阶段,一种称为部分FFT解调的方法被用来降低宽带声道的时间可变性。为了实现这一目标,将一个OFDM块的时间间隔分成几个部分间隔,使信道在每个较短的间隔内变化的机会较少,并且在每个间隔内分别进行解调。然后,在应用相干检测算法之前,将部分解调器输出组合在一起,其中进行精细的信道估计和数据检测。利用在3-7 km浅水信道上传输的10.515.5 kHz声学波段的实验数据,我们从数据检测均方误差(MSE)方面研究了接收机的性能,并表明所提出的算法具有优异的性能,超过了我们之前测试的所有方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Mitigating Channel Time Variation Effect in Acoustic OFDM Systems
OFDM systems are challenged by the time variability of mobile acoustic channels where the Doppler effect can be high enough that the received signal experiences non-negligible residual frequency offset, as well as channel time variability, which cause intercarrier interference (ICI). To mitigate these effects, we introduce an efficient yet computationally manageable two-stage algorithm that counteracts the frequency offset as well as the time selectivity of mobile acoustic channels. In the first stage, frequency offset is compensated using a practical approach based on differentially coherent detection which keeps the receiver complexity at a minimum and requires only a small pilot overhead. In the second stage, a method referred to as partial FFT demodulation is used to tone down the time variability of the broadband acoustic channel. Towards this goal, the time interval of one OFDM block is divided into several partial intervals, giving the channel less chance to change over each shorter interval, and demodulation is performed in each interval separately. The partial demodulator outputs are then combined before applying a coherent detection algorithm where refined channel estimation and data detection take place. Using the experimental data transmitted over a 3–7 km shallow water channel in the 10.515.5 kHz acoustic band, we study the receiver performance in terms of data detection mean squared error (MSE), and show that the proposed algorithm provides excellent performance, surpassing all our previously tested approaches.
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