Asymptotic Optimality of Binary Faster-than-Nyquist Signaling

Abstract

In this letter, the asymptotic information rate of faster-than-Nyquist (FTN) signaling is examined when the data sequence consists of independent and identically distributed (i.i.d.) binary symbols. It is shown that, as the FTN rate tends to infinity, the information rate converges to that of the FTN signaling with i.i.d. Gaussian symbols. This leads to the optimality of the i.i.d. binary FTN signaling in the sense that the channel capacity can be asymptotically achieved by employing a transmit pulse that results in the same power spectral density as the water-filling solution.