在脉冲噪声环境中用于快衰信道估计的改进型算法

该文分析了在存在噪声干扰的情况下，进行估计快衰信道的方法。在无线通信系统中，快衰信道可以采用AR(Auto-Regressive)模型进行预测，而LS (Least Square)算法和自适应Kalman滤波器可以分别对AR模型的参数和信道的冲激响应进行估计，但是这两种算法对噪声干扰非常敏感。该文提出改进型的RLM算法和Kalman 滤波器，并在存在噪声的情况下，使用它们并行对AR参数和信道的冲激响应进行联合估计。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，加快了待估的参数的收敛速度。

Estimation of Fast Fading Channel Using Enhanced Algorithms in Impulse Noise Environment

This paper analyzes the parallel estimation method of the fast fading channel in the present of impulse noise.In wireless system,the fast fading channel is typically modeled as the AR(Auto-Regressive)process.LS(Least Square)algorithm and adaptive Kalman filter are used to estimate the AR parameters and the channel impulse response respectively.The performance of these algorithms,however,is very sensitive to the impulse noise.In this paper,the enhanced RLM algorithm and adaptive Kalman filter are proposed and employed to jointly estimate the AR parameters and the channel impulse response under the impulse noise.Simulation results show that the coupled estimator using the enhanced RLM algorithm and Kalman filter has better convergence ability than conventional algorithms.