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Joint estimation of state and noise parameters in a linear dynamic system with impulsive measurement noise: Application to OFDM systems

机译：带有脉冲测量噪声的线性动态系统中状态和噪声参数的联合估计：在OFDM系统中的应用

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摘要

Interference mitigation is one of the main challenges in wireless communication, especially in ad hoc networks. In such context, the Multiple Access Interference (MAI) is known to be of an impulsive nature. Therefore, the conventional Gaussian assumption is inadequate to model this type of interference. Nevertheless, it can be accurately modeled by stable distributions. In fact, it was shown in literature that the alpha-stable distribution is a useful tool to model impulsive data. In this paper, we tackle the problem of noise compensation in ad hoc networks. More precisely, this issue is addressed within an Orthogonal Frequency Division Multiplexing (OFDM) transmission link assuming a symmetric alpha-stable model for the signal distortion due to MAI. Based on Bayesian estimation, the proposed approach estimates the transmitted OFDM symbols in the time domain using the Sequential Monte Carlo (SMC) methods. Unlike existing schemes, we consider the more realistic case where the impulsive noise parameters are assumed to be unknown at the receiver. Consequently, our approach deals also with the difficult task of noise parameters estimation which can be very useful for other purposes such as target tracking in wireless sensor networks or channel estimation. Simulations results, provided in terms of Mean Square Error (MSE) and Bit Error Rate (BER), illustrate the efficiency and the robustness of this scheme. (C) 2014 Elsevier Inc. All rights reserved.
机译：减轻干扰是无线通信中的主要挑战之一，尤其是在自组织网络中。在这种情况下，已知多址干扰（MAI）具有脉冲性质。因此，传统的高斯假设不足以对这种类型的干扰进行建模。但是，可以通过稳定的分布对其进行精确建模。实际上，文献表明，α稳定分布是用于模拟脉冲数据的有用工具。在本文中，我们解决了自组织网络中的噪声补偿问题。更准确地说，此问题在正交频分复用（OFDM）传输链路中得到解决，它假设对称的α稳定模型可用于MAI引起的信号失真。基于贝叶斯估计，所提出的方法使用顺序蒙特卡罗（SMC）方法在时域中估计发送的OFDM符号。与现有方案不同，我们考虑更现实的情况，其中假定在接收器处脉冲噪声参数未知。因此，我们的方法还处理了噪声参数估计这一艰巨的任务，该噪声参数估计对于其他目的（例如无线传感器网络中的目标跟踪或信道估计）非常有用。以均方误差（MSE）和误码率（BER）表示的仿真结果说明了该方案的效率和鲁棒性。 （C）2014 Elsevier Inc.保留所有权利。

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