A New Approximation Based on the Differential Evolution Algorithm for the Gaussian Q-function

This paper presents a new approach that combines two well-known approximations in order to improve the approximation accuracy of the Gaussian Q-function. Differential evolution, which can be considered as a simple and efficient evolutionary algorithm for optimizing real-valued optimization problems, is applied to estimate the parameters of the new approximation. The results produced by the presented approximation are compared with some other Q-function approaches from the literature. It is shown that the new approximation outperforms previously reported approximations and can provide an accurate representation of the Gaussian Q-function, especially for small arguments.