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基于多项式模型和卡尔曼滤波器的正交频分复用自适应信道估计算法

ISSN号：0469-5097
期刊名称：《南京大学学报：自然科学版》
时间：0
分类：TN919[电子电信—通信与信息系统;电子电信—信息与通信工程]
作者机构：[1]南京大学电子科学与工程系,南京210093
相关基金：国家自然科学基金（60832003）

关键词：多项式模型, 卡尔曼滤波器, 正交频分复用, 信道估计, polynomial regression model, Kalman filter, orthogonal frequency division multiplexing, channel estimation

中文摘要：

在正交频分复用（OFDM）系统中,为了准确地检测接收信号并实现解调,必须对信道的传输函数进行准确估计.本文提出了一种适用于OFDM通信系统,基于二阶多项式模型和卡尔曼滤波器（Kalman filter）的自适应信道估计算法.利用二阶多项式模型对无线时变信道进行建模,通过合理安排插入导频结构,使用块状导频,可以使得原本二维的时频多项式模型减少到一维,降低信道估计算法的复杂度.同时,在多项式模型的基础上,将时变无线信道等效为一autoregressive（AR）过程,从而建立起卡尔曼滤波器的过程方程与测量方程,通过卡尔曼滤波器的递推公式,即可实现对多项式模型参数的自适应估计.本文提出的算法可以仅使用最少的导频（即与多项式模型参数相同个数的导频）实现准确的信道估计.由于每次所需导频个数的减少,接收端所需存储的未解调信号的数量也随之降低,大幅减少了接收端所需的存储空间.计算机仿真证明,与线性插值算法和基于二阶多项式模型算法的信道估计相比,在相同输入信噪比和归一化多普勒频移条件下,本文提出的算法具有较低的误码率.

英文摘要：

For its excellent performance in combating multipath fading and efficiency in the use of available bandwidth,orthogonal frequency division multiplexing（OFDM） is considered as the most promising modulation scheme for wireless multimedia communications in frequency-selective channels.Various channel estimation algorithms for OFDM systems have been proposed in the past few years.In this paper,an adaptive OFDM channel estimation algorithm based on the second order regression model and Kalman filter is proposed.A second order regression model is used as an estimate of the time-variant fading channel.With a block type pilot arrangement,the original time-frequency 2-dimensional channel model is reduced to one dimension for operational simplicity.At the same time,the channel response is also modeled as an autoregressive process,through which the process equation and measurement equation of Kalman filter are established.Thus the recursive formulas of Kalman filter can be used to estimate the parameters of the regression model adaptively.The proposed algorithm can use the least pilot symbols,equivalent to the number of the parameters of the regression model,for the channel estimation,which reduces the capacity for storage of signals waiting for the demodulation at the receiver.The theoretical analysis and results of the computer simulation show that the proposed algorithm has a better performance compared with that of the linear interpolation algorithm and the channel estimation algorithm based on the regression model.

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