# Reduced Complexity Optimal Detection of Binary Faster-than-Nyquist Signaling

## TL;DR

This paper introduces a sphere decoding-based detection method for binary faster-than-Nyquist signaling that reduces computational complexity while maintaining optimal performance, enhancing data rate and spectral efficiency.

## Contribution

It proposes a novel sequence estimation technique exploiting FTN structure and noise correlation, achieving MLSE performance with lower complexity.

## Key findings

- SDSE matches MLSE performance
- Significant reduction in computational complexity
- FTN signaling greatly increases data rate and spectral efficiency

## Abstract

In this paper, we investigate the detection problem of binary faster-than-Nyquist (FTN) signaling and propose a novel sequence estimation technique that exploits its special structure. In particular, the proposed sequence estimation technique is based on sphere decoding (SD) and exploits the following two characteristics about the FTN detection problem: 1) the cor- relation between the noise samples after the receiver matched filter, and 2) the structure of the intersymbol interference (ISI) matrix. Simulation results show that the proposed SD-based sequence estimation (SDSE) achieves the optimal performance of the maximum likelihood sequence estimation (MLSE) at reduced computational complexity. This paper demonstrates that FTN signaling has the great potential of increasing the data rate and spectral efficiency substantially, when compared to Nyquist signaling, for the same bit-error-rate (BER) and signal-to-noise ratio (SNR).