时变信道下车载HDAF协作通信误码性能分析

车辆快速移动带来的信道时变特性降低了智能车载协作系统的误码性能。因此，该文提出了一种基于一阶自回归模型（AR1）的车载混合译码放大转发（HDAF）协作通信方法，该方法通过AR1的多普勒频偏相关系数来刻画时变信道特性，根据信道增益自适应选取HDAF协作通信方式，提升了智能交通系统的可控性安全。同时，分析了车载移动速度和信道状态信息（CSI）估计精度对误码性能的影响。数值分析表明，车载系统能通过增加CSI的估计精度，有效地减少车辆快速移动引起的误码平顶值。该方法相对于放大转发（AF）和解码转发（DF）协作通信方式，平均误码性能分别提高了约3.6 dB和1.5 dB。

Symbol-Error-Rate Performance Analysis of Hybrid Decode-Amplify-Forward Vehicular Cooperative Communication in Time-Varying Channel

Vehicle rapid movement causes time varying channel, which will reduce the symbol error rate (SER) performance of intelligent vehicular cooperative system. Based on first-order autoregressive (AR1) model, a hybrid decode amplify forward (HDAF) cooperative strategy is presented, where the characteristics of time- varying channel are described by correlation coefficient of Doppler shift. The proposed strategy can select adaptively cooperative approach according to the variation of channel gain, and thus the controllable security of intelligent transportation system is enhanced. Moreover, vehicular velocities and estimation precision of channel state information (CSI) are analyzed. Numerical results show that the improvement of the CSI estimation precision will reduce the error-floor-value caused by vehicle rapid movement. Compared to amplify and forward (AF) and decode and forward (DF) strategies, the SER performance of the proposed strategy can be increased about 3.6 dB and 1.5 dB, respectively.