中文摘要：

一个粒子过滤器被建议在多重输入的多重产量的直角的频率部门 multiplexing (MIMO-OFDM ) 执行搬运人频率偏移量(CFO ) 和隧道的联合评价无线通讯系统。它外面在顺序的重要性采样(SIS ) 从采样空格排斥隧道参数，并且与 Kalman 过滤器宣传他们。然后， CFO 粒子的重要性重量根据在测量和评价之间的错误的想象的部分被评估。粒子的变化被顺序的重要性物件 ampling (先生) 维持。模拟结果证明这个算法能与高精确性估计 CFO 和隧道参数。同时，当隧道模型有小变化时，一些坚韧性被保留。

英文摘要：

A particle filter is proposed to perform joint estimation of the carrier frequency offset （CFO） and the channel in multiple-input multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） wireless communication systems. It marginalizes out the channel parameters from the sampling space in sequential importance sampling （SIS）, and propagates them with the Kalman filter. Then the importance weights of the CFO particles are evaluated according to the imaginary part of the error between measurement and estimation. The varieties of particles are maintained by sequential importance resampling （SIR）. Simulation results demonstrate this algorithm can estimate the CFO and the channel parameters with high accuracy. At the same time, some robustness is kept when the channel model has small variations.