Previous Article in Journal
A Physics-Informed Neural Network (PINN) Approach to Over-Equilibrium Dynamics in Conservatively Perturbed Linear Equilibrium Systems
Previous Article in Special Issue
Continuous-Variable Quantum Key Distribution Based on N-APSK Modulation over Seawater Channel
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Entropy
Volume 28
Issue 1
10.3390/e28010010
entropy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Rate-Adaptive Information Reconciliation for CV-QKD Systems at Low Signal-to-Noise Ratios

by
Huiting Fu
1,
Jisheng Dai
1,
Yan Feng
2,
Han Hai
1,
Huayong Ge
1,*,
Peng Huang
3 and
Xue-Qin Jiang
1,*
1
College of Information and Intelligent Science, Donghua University, Shanghai 201620, China
2
College of Electronic and Information, Shanghai Dianji University, Shanghai 201306, China
3
State Key Laboratory of Advanced Optical Communication Systems and Networks, Institute for Quantum Sensing and Information Processing, Shanghai Jiao Tong University, Shanghai 200240, China
*
Authors to whom correspondence should be addressed.
Entropy 2026, 28(1), 10; https://doi.org/10.3390/e28010010 (registering DOI)
Submission received: 31 October 2025 / Revised: 17 December 2025 / Accepted: 19 December 2025 / Published: 20 December 2025
(This article belongs to the Special Issue Recent Advances in Continuous-Variable Quantum Key Distribution)
Versions Notes

Abstract

In continuous-variable quantum key distribution (CV-QKD) systems, information reconciliation (IR) is a crucial step that significantly affects the secret key rate (SKR). The fixed-rate error-correcting codes used in IR are highly sensitive to changes in the signal-to-noise ratio (SNR) and cannot maintain a high reconciliation efficiency in practical CV-QKD systems. To address this issue, we first propose a rate-adaptive IR protocol, namely Threshold-based IR (TIR), which changes the code rate of low-density parity-check (LDPC) codes by selectively revealing bits with lower reliability and adjusting their log-likelihood ratios (LLRs). Then, we propose a rate-adaptive IR protocol, namely Sorting-based IR (SIR), which not only adjusts the code rate according to variations in SNR, but also enables the CV-QKD systems to achieve high reconciliation efficiency over a wide range of SNRs. Furthermore, we perform an analysis of the protocols in terms of code rate, reconciliation efficiency, and complexity. The simulation results demonstrate that the proposed protocols outperform other rate-adaptive IR protocols, achieving a reconciliation efficiency higher than 98.5% in the SNR range below −20 dB and maintaining a certain SKR in long-distance transmission.
Keywords: continuous-variable quantum key distribution; information reconciliation; reconciliation efficiency; secret key rate; log-likelihood ratios continuous-variable quantum key distribution; information reconciliation; reconciliation efficiency; secret key rate; log-likelihood ratios

Share and Cite

MDPI and ACS Style

Fu, H.; Dai, J.; Feng, Y.; Hai, H.; Ge, H.; Huang, P.; Jiang, X.-Q. Rate-Adaptive Information Reconciliation for CV-QKD Systems at Low Signal-to-Noise Ratios. Entropy 2026, 28, 10. https://doi.org/10.3390/e28010010

AMA Style

Fu H, Dai J, Feng Y, Hai H, Ge H, Huang P, Jiang X-Q. Rate-Adaptive Information Reconciliation for CV-QKD Systems at Low Signal-to-Noise Ratios. Entropy. 2026; 28(1):10. https://doi.org/10.3390/e28010010

Chicago/Turabian Style

Fu, Huiting, Jisheng Dai, Yan Feng, Han Hai, Huayong Ge, Peng Huang, and Xue-Qin Jiang. 2026. "Rate-Adaptive Information Reconciliation for CV-QKD Systems at Low Signal-to-Noise Ratios" Entropy 28, no. 1: 10. https://doi.org/10.3390/e28010010

APA Style

Fu, H., Dai, J., Feng, Y., Hai, H., Ge, H., Huang, P., & Jiang, X.-Q. (2026). Rate-Adaptive Information Reconciliation for CV-QKD Systems at Low Signal-to-Noise Ratios. Entropy, 28(1), 10. https://doi.org/10.3390/e28010010

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop