Decision-Feedback Detection Strategy for Nonlinear Frequency-Division Multiplexing

TL;DR

This paper introduces a decision-feedback detection strategy for NFDM systems leveraging the causality property of the nonlinear Fourier transform, leading to significant performance improvements over traditional methods.

Contribution

It presents a novel detection approach tailored to the nonlinear Fourier transform's properties, enhancing NFDM system performance beyond existing techniques.

Findings

Significant Q-factor improvement demonstrated through simulations.

Theoretical bounds support the effectiveness of the proposed detection strategy.

Tailoring detection to nonlinear Fourier transform properties boosts NFDM performance.

Abstract

By exploiting a causality property of the nonlinear Fourier transform, a novel decision-feedback detection strategy for nonlinear frequency-division multiplexing (NFDM) systems is introduced. The performance of the proposed strategy is investigated both by simulations and by theoretical bounds and approximations, showing that it achieves a considerable performance improvement compared to previously adopted techniques in terms of Q-factor. The obtained improvement demonstrates that, by tailoring the detection strategy to the peculiar properties of the nonlinear Fourier transform, it is possible to boost the performance of NFDM systems and overcome current limitations imposed by the use of more conventional detection techniques suitable for the linear regime.