This article presents new and accurate approximations for the Gaussian
Q-function, which is an important tool in the field of communication theory. A
genetic algorithm was employed to find the optimum coefficients of the proposed
approximations. The accuracy of the new approximations was examined and
compared with those of previous works in the literature. It was shown that the
presented high-order exponential approximations provide better accuracy
compared to the previously introduced approximations, in general, at the cost
of slightly increased mathematical complexity.
This article presents new and accurate approximations for the Gaussian Q-function, which is an important tool in the field of communication theory. A genetic algorithm was employed to find the optimum coefficients of the proposed approximations. The accuracy of the new approximations was examined and compared with those of previous works in the literature. It was shown that the presented high-order exponential approximations provide better accuracy compared to the previously introduced approximations, in general, at the cost of slightly increased mathematical complexity.
