现有的4G网络频偏估计算法在高速车载环境下，存在较大的估计误差和较高的复杂度等问题。为此，提出一种基于多个车载节点协同工作的频偏估计算法。使用各节点强径的测量信噪比和角度特征进行加权估计，提高各协同节点频偏估计的准确度。对高速运动的OFDM系统进行蒙特卡洛仿真及对协同估计模型进行数值分析，结果表明，该算法能够有效改善LTE传输系统的误码率性能。%Due to great carrier frequency deviation under high speed vehicular wireless environment in 4G network, the existing estimation algorithms perform ineffectively in terms of complexity and the estimated error. This paper proposes a dynamic cooperative frequency offset estimation algorithm. This estimation algorithm uses a weighted frequency offset estimation model for each receiver. The model not only allows for the weight of Signal to Interference plus Noise Ratio(SINR)but includes the weight of strong path signal. Monte-Carlo method is used to simulate the vehicular Orthogonal Frequency Division Multiplexing(OFDM) system. Numerical results of cooperation model are compared with conventional algorithms. Results show that the cooperative estimation algorithm can improve performance of error rate for Long Term Evolution(LTE) system.
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