Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution

Farah Al-sallami; Sujan Rajbhandari; Zahir Ahmad; David  Grace

Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution

Farah Al-sallami
, Sujan Rajbhandari
, Zahir Ahmad
, David Grace

School of Computer Science & Engineering

York University
Coventry University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In local local oscillator (LLO)-based continuous-
variable quantum key distribution (CV-QKD), a difference between
the linewidth values of two free-running lasers at Alice and Bob
induces a phase drift noise. This work proposes a novel minimax
filter-based phase tracking that aims to minimize the phase drift
considering maximum residual phase error to achieve optimal
phase estimation. Simulation results show that the minimax filter
offers a lower phase estimation mean square error (MSE) value
compared to the Kalman filter when worst-case phase drift error
due to high linewidth difference or high measurement noise values
are considered.

Original language	English
Title of host publication	13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)
Pages	499-502
Publication status	Published - 1 Sept 2022

Cite this

@inproceedings{78f282bd17b242369971a4edcf57ba6b,

title = "Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution",

abstract = "In local local oscillator (LLO)-based continuous- variable quantum key distribution (CV-QKD), a difference between the linewidth values of two free-running lasers at Alice and Bob induces a phase drift noise. This work proposes a novel minimax filter-based phase tracking that aims to minimize the phase drift considering maximum residual phase error to achieve optimal phase estimation. Simulation results show that the minimax filter offers a lower phase estimation mean square error (MSE) value compared to the Kalman filter when worst-case phase drift error due to high linewidth difference or high measurement noise values are considered.",

author = "Farah Al-sallami and Sujan Rajbhandari and Zahir Ahmad and David Grace",

year = "2022",

month = sep,

day = "1",

language = "English",

pages = "499--502",

booktitle = "13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)",

}

Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution. / Al-sallami, Farah; Rajbhandari, Sujan; Ahmad, Zahir et al.
13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). 2022. p. 499-502.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution

AU - Al-sallami, Farah

AU - Rajbhandari, Sujan

AU - Ahmad, Zahir

AU - Grace, David

PY - 2022/9/1

Y1 - 2022/9/1

N2 - In local local oscillator (LLO)-based continuous- variable quantum key distribution (CV-QKD), a difference between the linewidth values of two free-running lasers at Alice and Bob induces a phase drift noise. This work proposes a novel minimax filter-based phase tracking that aims to minimize the phase drift considering maximum residual phase error to achieve optimal phase estimation. Simulation results show that the minimax filter offers a lower phase estimation mean square error (MSE) value compared to the Kalman filter when worst-case phase drift error due to high linewidth difference or high measurement noise values are considered.

AB - In local local oscillator (LLO)-based continuous- variable quantum key distribution (CV-QKD), a difference between the linewidth values of two free-running lasers at Alice and Bob induces a phase drift noise. This work proposes a novel minimax filter-based phase tracking that aims to minimize the phase drift considering maximum residual phase error to achieve optimal phase estimation. Simulation results show that the minimax filter offers a lower phase estimation mean square error (MSE) value compared to the Kalman filter when worst-case phase drift error due to high linewidth difference or high measurement noise values are considered.

M3 - Conference contribution

SP - 499

EP - 502

BT - 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)

ER -

Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution

Abstract

Fingerprint

Cite this