强脉冲噪声环境下的多径衰信道估计

提出一种在强干扰脉冲噪声存在下对无线多径信道进行估计的算法.在无线通信系统中,衰落信道可以采用自回归(AR)模型建模,通过RLS算法和自适应Kalman滤波器分别对AR模型的参数进行估计,但是,这两种算法对噪声干扰非常敏感.为了加快RLS算法的收敛性,并有效抑制大脉冲干扰的影响,在算法的改进中引入了抑制因子,用于对脉冲干扰幅度的抑制.仿真结果显示:相比于传统的算法,改进后的算法在联合估计信道时,提高了抵抗大脉冲干扰的能力,加快了待估参数的收敛速度.

Multi-path Channel Estimation in Strong Impulse Noise Environment

A new method for on-line identification of multi-path channels on strong impulse noise is presented.The fading channel in the wireless communication system is typically modeled as autoregressive(AR)process.Recursive least square(RLS)algorithm and adaptive Kalman filter are used to estimate the AR parameters and the channel impulse response,respectively.The performances of these algorithms are sensitive to the impulse noise.To strengthen the ability of resisting the impulse noise,a new suppressive factor is proposed to suppress the amplitude of the impulse and improve the ability of the convergence speed.Simulation results show that the coupled estimator using the improved RLS algorithm and Kalman filter is more robust against the consecutive impulse noise,and has better convergence ability than conventional algorithms.