mlsanityData to 14 Oct 2026

Cost-Gain Analysis of Sequence Selection for Nonlinearity Mitigation

arXiv 2411.02004 ↗First posted 4 Nov 2024cs.IT eess.SP math.ITcited by 2

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Abstract (arXiv)

We propose a low-complexity sign-dependent metric for sequence selection and study the nonlinear shaping gain achievable for a given computational cost, establishing a benchmark for future research. Small gains are obtained with feasible complexity. Higher gains are achievable in principle, but with high complexity or a more sophisticated metric.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Nov 2024.

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Citing papers per year: 2025: 1; 2026: 1.

2 papers.