High-SNR Asymptotics of Mutual Information for Discrete Constellations

The high-signal-to-noise ratio (SNR) asymptotic behavior of the mutual information (MI) for discrete constellations over the scalar additive white Gaussian noise channel is studied. Exact asymptotic expressions for the MI for arbitrary one-dimensional constellations and input distributions are presented in the limit as the SNR tends to infinity. Using the relationship between the MI and the minimum mean-square error (MMSE), asymptotics of the MMSE are also developed. It is shown that for any input distribution, the MI and the MMSE have an asymptotic behavior proportional to a Gaussian Q-function, whose argument depends only on the minimum Euclidean distance of the constellation and the SNR. Closed-form expressions for the coefficients of these Q-functions are calculated