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Performance of Iterated EKF Technique to Estimate Time Varying Channel Using Pilot Assisted Method in MIMO-OFDM System

机译:MIMO-OFDM系统中使用导频辅助方法的迭代EKF技术估计时变信道的性能

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In this paper Iterative Extended Kalman Filter (IEKF) technique has been proposed to estimate the time varying channel for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing systems (OFDM). Channel state information (CSI) plays major role to improve the performance of any wireless communication system for different fading channels to detect the data. Kalman Filter (KF) is most powerful technique for linear processing and it is more suitable to estimate additive white gaussian noise (AWGN) channels. But it is not fit for non-linear problems since wireless channels have some nonlinear characteristics. In this paper, IEKF technique has been proposed to estimate time varying channel, and comparative analysis has been done with the techniques which are proposed based on LS, MMSE and EKF. Simulations also demonstrated that, channel estimation based on IEKF having significant improvement in aspect of bit error rate (BER) and mean square error (MSE) with modest computational complexity
机译:本文提出了迭代扩展卡尔曼滤波器(IEKF)技术来估计多输入多输出(MIMO)正交频分复用系统(OFDM)的时变信道。信道状态信息(CSI)在提高任何无线通信系统针对不同衰落信道检测数据的性能方面起着重要作用。卡尔曼滤波器(KF)是最强大的线性处理技术,它更适合于估计加性高斯白噪声(AWGN)通道。但这不适用于非线性问题,因为无线信道具有某些非线性特征。本文提出了IEKF技术来估计时变信道,并与基于LS,MMSE和EKF提出的技术进行了比较分析。仿真还表明,基于IEKF的信道估计在误码率(BER)和均方误差(MSE)方面均具有显着改善,并且计算复杂度较低

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