摘要
OFDM作为下一代通信系统的关键技术,亟需解决其同步问题。在ML算法的基础上,提出了基于多符号的ML同步算法。在加性高斯白噪声条件下进行了仿真,结果表明改进的同步算法性能比ML算法要好很多。其中,基于连续符号的定时估计方法 1在信噪比超过2 dB时准确率几乎可达100%,基于重复发送符号的定时估计方法 2在较低信噪比条件下性能比方法 1更好。信噪比为-8 dB左右时,3种优化的频偏估计方法的估计误差均在1%以内,明显好于ML频偏估计算法,证明了改进算法的优越性。
As the key technology of the next generation communication system,OFDM has to solve the problems of synchronization.Based on the ML algorithm theory,a multi-symbol ML algorithm is proposed.Under the condition with AWGN,the simulation results explain the optimized algorithm can reach much better performance.When the SNR is bigger than 2 dB the first timing synchronization method based on continuous symbols can completely estimate the right starting time of symbols.When the SNR is small,the performance of the second method based on repeated symbols is better than the first one.When the SNR reaches around-8 dB the frequency offset deviations of the three optimized frequency estimation methods are less than 1％.The superiority is obvious which demonstrates the proposed algorithm is excellent.
出处
《电子技术应用》
北大核心
2014年第3期97-100,共4页
Application of Electronic Technique
关键词
正交频分复用
最大似然估计
定时估计
频偏估计
OFDM
ML estimation
time synchronization estimation
frequency synchronization estimation
