The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 FDD MIMO(Multiple-Input and Multiple-Output) 시스템을 위한 딥러닝 기반 비밀키 생성 기법을 제안한다. 우리는 업링크와 다운링크 채널 간의 매핑 관계를 학습하기 위해 무선 환경을 특성화하기 위해 인코더-디코더 기반 컨벌루션 신경망을 구축했습니다. 설계된 신경망은 어떠한 정보 피드백 없이 추정된 업링크 채널 상태 정보를 기반으로 다운링크 채널 상태 정보를 정확하게 예측할 수 있다. 신경망에 의해 예측된 다운링크 채널 응답으로부터 무작위 비밀 키가 생성될 수 있습니다. 시뮬레이션 결과는 딥러닝 기반 SKG 방식이 키 합의 비율과 달성 가능한 비밀 키 비율 측면에서 상당한 성능 향상을 달성할 수 있음을 보여줍니다.
Zheng WAN
Information Engineering University
Kaizhi HUANG
Information Engineering University
Lu CHEN
Information Engineering University
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부
Zheng WAN, Kaizhi HUANG, Lu CHEN, "Secret Key Generation Scheme Based on Deep Learning in FDD MIMO Systems" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 7, pp. 1058-1062, July 2021, doi: 10.1587/transinf.2020EDL8145.
Abstract: In this paper, a deep learning-based secret key generation scheme is proposed for FDD multiple-input and multiple-output (MIMO) systems. We built an encoder-decoder based convolutional neural network to characterize the wireless environment to learn the mapping relationship between the uplink and downlink channel. The designed neural network can accurately predict the downlink channel state information based on the estimated uplink channel state information without any information feedback. Random secret keys can be generated from downlink channel responses predicted by the neural network. Simulation results show that deep learning based SKG scheme can achieve significant performance improvement in terms of the key agreement ratio and achievable secret key rate.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020EDL8145/_p
부
@ARTICLE{e104-d_7_1058,
author={Zheng WAN, Kaizhi HUANG, Lu CHEN, },
journal={IEICE TRANSACTIONS on Information},
title={Secret Key Generation Scheme Based on Deep Learning in FDD MIMO Systems},
year={2021},
volume={E104-D},
number={7},
pages={1058-1062},
abstract={In this paper, a deep learning-based secret key generation scheme is proposed for FDD multiple-input and multiple-output (MIMO) systems. We built an encoder-decoder based convolutional neural network to characterize the wireless environment to learn the mapping relationship between the uplink and downlink channel. The designed neural network can accurately predict the downlink channel state information based on the estimated uplink channel state information without any information feedback. Random secret keys can be generated from downlink channel responses predicted by the neural network. Simulation results show that deep learning based SKG scheme can achieve significant performance improvement in terms of the key agreement ratio and achievable secret key rate.},
keywords={},
doi={10.1587/transinf.2020EDL8145},
ISSN={1745-1361},
month={July},}
부
TY - JOUR
TI - Secret Key Generation Scheme Based on Deep Learning in FDD MIMO Systems
T2 - IEICE TRANSACTIONS on Information
SP - 1058
EP - 1062
AU - Zheng WAN
AU - Kaizhi HUANG
AU - Lu CHEN
PY - 2021
DO - 10.1587/transinf.2020EDL8145
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2021
AB - In this paper, a deep learning-based secret key generation scheme is proposed for FDD multiple-input and multiple-output (MIMO) systems. We built an encoder-decoder based convolutional neural network to characterize the wireless environment to learn the mapping relationship between the uplink and downlink channel. The designed neural network can accurately predict the downlink channel state information based on the estimated uplink channel state information without any information feedback. Random secret keys can be generated from downlink channel responses predicted by the neural network. Simulation results show that deep learning based SKG scheme can achieve significant performance improvement in terms of the key agreement ratio and achievable secret key rate.
ER -