Conventional timing estimation schemes based on autocorrelation experience performance degradation in the multipath channel environment with high delay spread. To overcome this problem, we proposed an improvement of the timing estimation for the OFDM system based on statistical change of symmetrical correlator. The new method uses iterative normalization technique to the correlator output before the detection based on statistical change of symmetric correlator is applied. Thus, it increases the detection probability and achieves better performance than previously published methods in the multipath environment. Computer simulation shows that our method is very robust in the fading multipath channel. are supporting applications that run in a high speed mobility environment. Recently OFDM technique is also used for cognitive radio systems, which the use of frequency spectrum in the OFDM systems can be done as efficiently as possible [4]- [5]. However, OFDM systems need strict timing synchronization between transmitter and receiver, as an error in timing estimation give rise to InterSymbol Interference (ISI) and can decrease the overall performance of OFDM systems [6]- [7].For symbol timing estimation, Schmidl [8] used a preamble consists of two identical parts for symbol timing estimation. But, the timing metric of Schmidl's method has a plateau, which causes a large variance in the timing offset estimation. To decrease the plateau, Minn [9] proposed a new training symbol with four identical parts. It results a sharper timing metric than Schmidl's method, however, it still has ambiguity due to some side-lobes at a side of the peak correlation region, thus estimation variance is still large. In order to reduce the variance, Park [10] proposed a sharper timing metric using symmetric correlation property of the preamble. Yet, the timing metric of Park's method has two large side-lobes. To eliminate the side-lobes of Park's timing metric, Yi [11] proposed a new preamble structure that has symmetric correlation property. The performance of all the above-mentioned approaches decrease in multipath channel environments.To overcome this problem, Cho [12] proposed a method that exploits statistical change of symmetric correlator. It reduces the multipath channel effect, hence the variance of the timing offset estimation is small. However, Cho's method generates error detection if the correlation magnitude on the first arriving path is much smaller than the strongest path. To overcome this problem, we proposed an iterative normalization technique to the correlator output before the detection based on statistical change of symmetric correlator is applied. Considering the very small correlation magnitude on the first arriving path, we attempt to increase the correlation magnitude on the first arriving path to