一种低复杂性的最大似然信道估计器在IEEE802.16a中的应用

A Low-Complexity ML Channel Estimator in IEEE 802.16a

研究了一种应用于IEEE802.16aOFDM(正交频分复用)系统的低复杂性最大似然信道估计器,并与LS估计、MMSE估计的BER、MSE性能及其计算复杂度进行了比较,仿真结果表明,此估计器能够极大的减小计算的复杂性并能达到较好的性能。

In this paper, a low-complexity ML channel estimator used in IEEE 802.16a OFDM systems is studied.We compare it with some other estimators in computational complexity,such as LS and MMSE in BER,and MSE.Simulation shows that the ML estimator has a good performance with a low complexity.