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首页> 外文期刊>EURASIP journal on advances in signal processing >Non-Pilot-Aided Sequential Monte Carlo Method toJoint Signal, Phase Noise, and Frequency Offset Estimationin Multicarrier Systems
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Non-Pilot-Aided Sequential Monte Carlo Method toJoint Signal, Phase Noise, and Frequency Offset Estimationin Multicarrier Systems

机译:非飞行员辅助顺序蒙特卡罗方法联合多载波系统中的信号,相位噪声和频率偏移估计

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摘要

We address the problem of phase noise (PHN) and carrier frequency offset (CFO) mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE) and the intercarriei interference (ICI) which severely degrade the accuracy of the symbol detection stage Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER) and mean square error (MSE) to illustrate the efficiency and the robustness of the proposed algorithm.
机译:我们解决了多载波接收机中相位噪声(PHN)和载波频率偏移(CFO)缓解的问题。在多载波系统中,相位失真会产生两个影响:共相位误差(CPE)和载波间干扰(ICI),这会严重降低符号检测级的准确性。在此,我们提出了一种非飞行员辅助方案来共同估算PHN, CFO和时域中的多载波信号。与现有方法不同,无需任何决策指导的方案即可执行基于非飞行员的估计。我们针对此问题的方法基于贝叶斯估计,该贝叶斯估计使用顺序蒙特卡洛滤波(通常称为粒子滤波)。通过结合Rao-Blackwellization技术的原理和相位失真采样的近似最佳重要性函数,可以有效地实现粒子滤波器。此外,为了充分利用时域处理的优势,我们提出了一种多载波信号模型,该模型包含了循环前缀引起的冗余信息,从而显着提高了性能。根据误码率(BER)和均方误差(MSE)提供了仿真结果,以说明所提出算法的效率和鲁棒性。

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