In this paper, we investigate the problem of testing the equality of two distributions by integrating the squared norm of the difference between two corresponding empirical characteristic functions. This results in a linear combination of three different U-statistics. So the original testing problem is reduced to testing whether this linear combination is zero or not. We apply the jackknife empirical likelihood (JEL) method to the new hypothesis testing problem. It has been proved that, under multivariate case, the log JEL statistic after scaling tends to a chi-square distribution with degree of freedom 1. Simulation studies are presented to assess the finite sample performance of our method.