摘要
依据数据辅助类算法传输效率较低,盲估计算法精度较差的特性,通过重构理想状态下的时域接收信号,提出一种基于信号重构的CFO估计算法。该算法既具备盲估计算法计算简单的特点,又能实现数据辅助类算法的精确性。由于对辅助数据不作要求,在精度要求不高的情况下,可以直接进行盲估计。而如果需要提升性能,则可以通过增加训练符号的方式来实现。最后,通过Matlab仿真验证了本算法的性能,结果表明,本算法的抗干扰性能较好,且随着采样数的增加,算法的估计精度也相应地得到了提升。
Analyzing the characteristics of low data transportation efficiency of data-aided algorithm, and relatively worse performance of blind estimation, it proposed a new CFO estimation algorithm based on signal reconstruction. This algorithm can both realize the performance of data-aided algorithm and simplify the computational complexity at the same time. Not requiring the training sequences, this algorithm can be used in differently circumstances. To improve its precision, CP or pilot can be inserted. When persuing low complexity, the data symbols can be directly used to estimate the CFO. Finally, matlab is used to build a simulation platform to test the performance of this algorithm. Results show that this algorithm has robust performance to resist outside interference, and when sampling accounts arise, its performance was accordingly improved.
出处
《邮电设计技术》
2015年第11期54-58,共5页
Designing Techniques of Posts and Telecommunications
