OFDM系统中一种基于训练引导的判决反馈均衡技术

Training Guided Decision Feedback Equalization Method for OFDM System

针对OFDM系统,提出了一种基于训练引导的判决反馈均衡算法。算法中的信道估计以基于长训练序列的初始估计为基础,结合判决过程中所反映出的信道变化情况而综合得到。并将当前信道的预测值反馈回去,用以对接收的下一个数据符号进行均衡。通过仿真,测试了算法的误符号性能,并与常规的单一训练序列算法和基于导频的线性插值算法进行了比较。仿真结果表明,该算法可以很好的抵抗多径时延扩展和多普勒频移对接收信号的影响,均衡后的误符号性能较单一训练序列算法有3～4dB的性能改善,并能在最大多普勒频移高达275Hz范围内的高速移动环境下对信道衰落实施有效的估计和均衡。

A training guided decision feedback equalization （DFE） method was proposed for OFDM system. The channel estimation was obtained based on the initial estimation from the long training sequence combined with the channel variation derived by the decision process. And the corresponding prediction of the channel response was feedback to equalize following received data symbols. Simulation was employed to evaluate the symbol error rate （SER） of the algorithm, and it was compared with the single long training sequence based channel estimation and pilot sub-carrier based linear interpolation channel estimation method. Simulation indicates that the proposed algorithm can effectively combat the fading in received signals caused by the multi-path propagation and Doppler shift, and can achieve a 3 to 4 dB SER performance gain to the single long training sequence based channel estimation. The implementation in high speed mobile circumstance with the maximum Doppler shift up to 275 Hz is also applicable.