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研究了OFDM系统中的最大似然估计(ML)算法,并使用数据循环移位以及多符号联合估计等技术对ML算法进行了改进,随后提出了一个综合性的新方案。仿真结果显示,在AWGN和瑞利多径衰落信道中,该方案可以有效提高符号定时偏差(STO)和载波频率偏移(CFO)的估计性能。
The Maximum Likelihood Estimation (ML) algorithm in OFDM system is studied. The ML algorithm is improved by using data cyclic shift and multi-symbol joint estimation, and then a new integrated scheme is proposed. The simulation results show that this scheme can effectively improve the estimation performance of STO and CFO in AWGN and Rayleigh multipath fading channels.