scholarly journals Continuous-Variable Error Correction for General Gaussian Noises

2021 ◽  
Vol 15 (3) ◽  
Author(s):  
Jing Wu ◽  
Quntao Zhuang
2020 ◽  
Vol 22 (2) ◽  
pp. 022001 ◽  
Author(s):  
Quntao Zhuang ◽  
John Preskill ◽  
Liang Jiang

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kadir Gümüş ◽  
Tobias A. Eriksson ◽  
Masahiro Takeoka ◽  
Mikio Fujiwara ◽  
Masahide Sasaki ◽  
...  

AbstractReconciliation is a key element of continuous-variable quantum key distribution (CV-QKD) protocols, affecting both the complexity and performance of the entire system. During the reconciliation protocol, error correction is typically performed using low-density parity-check (LDPC) codes with a single decoding attempt. In this paper, we propose a modification to a conventional reconciliation protocol used in four-state protocol CV-QKD systems called the multiple decoding attempts (MDA) protocol. MDA uses multiple decoding attempts with LDPC codes, each attempt having fewer decoding iteration than the conventional protocol. Between each decoding attempt we propose to reveal information bits, which effectively lowers the code rate. MDA is shown to outperform the conventional protocol in regards to the secret key rate (SKR). A 10% decrease in frame error rate and an 8.5% increase in SKR are reported in this paper. A simple early termination for the LDPC decoder is also proposed and implemented. With early termination, MDA has decoding complexity similar to the conventional protocol while having an improved SKR.


2017 ◽  
Vol 15 (08) ◽  
pp. 1740028 ◽  
Author(s):  
Fred Daneshgaran ◽  
Marina Mondin ◽  
Khashayar Olia

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal-to-Noise Ratio (SNR) exasperating the problem. Quantization over higher dimensions is advantageous since it allows for fractional bit per sample accuracy which may be needed at very low SNR conditions whereby the achievable secret key rate is significantly less than one bit per sample. In this paper, we propose to use Permutation Modulation (PM) for quantization of Gaussian vectors potentially containing thousands of samples. PM is applied to the magnitudes of the Gaussian samples and we explore the dependence of the sign error probability on the magnitude of the samples. At very low SNR, we may transmit the entire label of the PM code from Bob to Alice in Reverse Reconciliation (RR) over public channel. The side information extracted from this label can then be used by Alice to characterize the sign error probability of her individual samples. Forward Error Correction (FEC) coding can be used by Bob on each subset of samples with similar sign error probability to aid Alice in error correction. This can be done for different subsets of samples with similar sign error probabilities leading to an Unequal Error Protection (UEP) coding paradigm.


2017 ◽  
Vol 19 (2) ◽  
pp. 023003 ◽  
Author(s):  
Sarah J Johnson ◽  
Andrew M Lance ◽  
Lawrence Ong ◽  
Mahyar Shirvanimoghaddam ◽  
T C Ralph ◽  
...  

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Shuhong Hao ◽  
Xiaolong Su ◽  
Caixing Tian ◽  
Changde Xie ◽  
Kunchi Peng

2021 ◽  
Author(s):  
Shuhong Hao ◽  
Xiaowei Deng ◽  
Yang Liu ◽  
Xiaolong Su ◽  
Changde Xie ◽  
...  

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