Constrained Capacity Analysis for Faster-than-Nyquist Signaling

2026-07-07

AI Summary

This study addresses the ambiguity in the constrained channel capacity of faster-than-Nyquist (FTN) signaling under finite-alphabet inputs by introducing cyclic prefixes and suffixes, which—combined with the discrete Fourier transform (DFT)—decompose the FTN channel into parallel eigen-subchannels. The authors derive, for the first time, a systematic expression for the constrained capacity under such conditions. Their analysis reveals that at moderate to low signal-to-noise ratios, small constellations with aggressive time acceleration can outperform larger constellations with mild acceleration. While spectral efficiency benefits from time acceleration, it remains fundamentally limited by constellation size. Furthermore, the work formulates an achievable information rate under mismatched decoding and demonstrates that adaptive bit loading across high-quality eigen-subchannels effectively approaches the derived capacity limit.

Abstract

This paper studies the constrained-capacity for precoded faster-than-Nyquist (FTN) signaling with finite-alphabet inputs. Despite the promise of accelerated transmission, the fundamental rate limit of precoded FTN signaling under practical finite-alphabet constraints remains unclear. By introducing cyclic prefix (CP) and cyclic suffix (CS), the FTN channel is decomposed into a set of parallel eigenchannels by the discrete Fourier transform (DFT) matrix, based on which the constrained capacity is derived. The results demonstrate that time acceleration can improve spectral efficiency over Nyquist signaling even when a fixed modulation order is employed. Moreover, in the low and moderate signal-to-noise ratio (SNR) regimes, a smaller constellation combined with stronger time acceleration can outperform a larger constellation with weaker acceleration. Next, the asymptotic behavior of the constrained capacity is analyzed as the acceleration factor tends to zero under both fixed transmit-SNR and fixed receive-SNR definitions. It is shown that the constrained capacity for DFT-precoded FTN is fundamentally limited by the constellation size. In addition, the constrained capacity under channel mismatch is studied and a mismatched achievable information rate (AIR) formulation is developed to show the effects of practical constraints on the performance degradation. Finally, adaptive bit loading across eigenchannels is investigated to exploit the higher-quality eigenchannels.

Problem

• constrained capacity
• faster-than-Nyquist signaling
• finite-alphabet inputs
• spectral efficiency
• channel mismatch

Innovation

• Faster-than-Nyquist signaling
• Constrained capacity
• DFT precoding
• Finite-alphabet inputs
• Eigenchannel decomposition