基于点密度优化的以太网眼图参数计算方法

传统以太网眼图参数计算算法是建立在高斯模型点密度统计的基础之上，是在假定眼图累积次数足够多、点分布足够密集、眼图垂直片段上的电压分布具有拟合高斯正态分布等条件下计算而得。当眼图累积的次数较少、点分布不够密集、垂直片段上的电压分布不具有拟合高斯正态分布时，眼图参数计算结果就会存在较大误差。基于此，提出基于点密度优化的以太网眼图参数计算方法，实验结果表明，该方法能较准确地计算出眼图中的眼幅度和上升/下降时间，有效克服了眼图累积次数较少、点分布不够密集对眼图参数计算的影响。

Calculation method of Ethernet eye parameters based on optimal point density

The traditional Ethernet eye parameters calculation algorithm is based on the Gauss model of point density statistics. The algorithm assumes that the cumulative frequencies of eye diagram are enough, the distribution of points is sufficiently dense and the voltage distribution of eye vertical fragment fits the Gauss normal distribution. But when the cumulative frequencies of eye diagram are less, the distribution of points is not dense and the voltage distribution on the vertical section does not fit Gauss normal distribution, the results of eye diagram parameters will be a big error. Based on this, this paper puts forward the optimization calculation method of Ethernet eye diagram parameters based on point density. Experimental results show that, this method can calculate the eye amplitude and rise/fall time accurately, and solve the problem of less eye cumulative number and points distributed in the eye diagram parameter calculation effectively.