基于共轭数据重排的信道预测算法

Channel Prediction Algorithm Based on Conjugate Data Rearrangement

为提高预测的精确度,在分析基本ESPR IT(Estim ation S ignal Param eters via Rotational Invariance Tech-n iques)缺点的基础上,提出了一种共轭数据重排的ESPR IT信道预测算法。针对实际中平坦快速衰落信道系数为复数的特点,通过对采样数据的共轭重排,使被利用的数据长度等效于增加了1倍。仿真实验表明,该算法在运算量基本保持不变的情况下与基本ESPR IT相比,提高了信道预测的精确度。

In order to improve the prediction veracity, the shortcoming of the basic ESPRIT （Estimation Signal Parameters via Rotational Invariance Techniques） algorithm is analyzed and an ESPRIT channel prediction algorithm based on conjugate data rearrangement is proposed. In fact, the flat fast fading channels coefficient is complex number. The sampling data are conjugate arranged so that the length of the data are equal to double. Simulation results show that prediction veracity is improved and operation quantity is almost invariable compared with the basic EPRIT algorithm.