Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel

Jianzhong Lu; Dongxuan He; Zhaocheng Wang

doi:10.1109/VTC2021-Spring51267.2021.9448708

Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel

Jianzhong Lu, Dongxuan He, Zhaocheng Wang

Tsinghua University

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

2 Citations (Scopus)

Abstract

In this paper, we investigate secure relay selection for finite-state Markov channel and propose a Q-learning assisted relay selection scheme. Specifically, we firstly analyze the achievable effective secrecy throughput of random selection scheme and optimal selection scheme, respectively, showing that the secrecy performance is highly determined by relay selection methodology. Then, we leverage the Q-learning to learn how to select relay for finite-state Markov channel, which is capable of selecting proper relay with outdated channel state information. Numerical results demonstrate that our proposed Q-learning assisted relay selection scheme can achieve a significant improvement of effective secrecy throughput even with outdated channel information.

Original language	English
Title of host publication	2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728189642
DOIs	https://doi.org/10.1109/VTC2021-Spring51267.2021.9448708
Publication status	Published - Apr 2021
Externally published	Yes
Event	93rd IEEE Vehicular Technology Conference, VTC 2021-Spring - Virtual, Online Duration: 25 Apr 2021 → 28 Apr 2021

Publication series

Name	IEEE Vehicular Technology Conference
Volume	2021-April
ISSN (Print)	1550-2252

Conference

Conference	93rd IEEE Vehicular Technology Conference, VTC 2021-Spring
City	Virtual, Online
Period	25/04/21 → 28/04/21

Access to Document

10.1109/VTC2021-Spring51267.2021.9448708

Cite this

Lu, J., He, D., & Wang, Z. (2021). Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel. In 2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings Article 9448708 (IEEE Vehicular Technology Conference; Vol. 2021-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTC2021-Spring51267.2021.9448708

@inproceedings{a8d8db0ca606451b9fdf6278b6f56fc3,

title = "Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel",

abstract = "In this paper, we investigate secure relay selection for finite-state Markov channel and propose a Q-learning assisted relay selection scheme. Specifically, we firstly analyze the achievable effective secrecy throughput of random selection scheme and optimal selection scheme, respectively, showing that the secrecy performance is highly determined by relay selection methodology. Then, we leverage the Q-learning to learn how to select relay for finite-state Markov channel, which is capable of selecting proper relay with outdated channel state information. Numerical results demonstrate that our proposed Q-learning assisted relay selection scheme can achieve a significant improvement of effective secrecy throughput even with outdated channel information.",

author = "Jianzhong Lu and Dongxuan He and Zhaocheng Wang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring ; Conference date: 25-04-2021 Through 28-04-2021",

year = "2021",

month = apr,

doi = "10.1109/VTC2021-Spring51267.2021.9448708",

language = "English",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings",

address = "United States",

}

Lu, J, He, D & Wang, Z 2021, Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel. in 2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings., 9448708, IEEE Vehicular Technology Conference, vol. 2021-April, Institute of Electrical and Electronics Engineers Inc., 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring, Virtual, Online, 25/04/21. https://doi.org/10.1109/VTC2021-Spring51267.2021.9448708

Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel. / Lu, Jianzhong; He, Dongxuan; Wang, Zhaocheng.
2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. 9448708 (IEEE Vehicular Technology Conference; Vol. 2021-April).

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

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AU - Lu, Jianzhong

AU - He, Dongxuan

AU - Wang, Zhaocheng

PY - 2021/4

Y1 - 2021/4

N2 - In this paper, we investigate secure relay selection for finite-state Markov channel and propose a Q-learning assisted relay selection scheme. Specifically, we firstly analyze the achievable effective secrecy throughput of random selection scheme and optimal selection scheme, respectively, showing that the secrecy performance is highly determined by relay selection methodology. Then, we leverage the Q-learning to learn how to select relay for finite-state Markov channel, which is capable of selecting proper relay with outdated channel state information. Numerical results demonstrate that our proposed Q-learning assisted relay selection scheme can achieve a significant improvement of effective secrecy throughput even with outdated channel information.

AB - In this paper, we investigate secure relay selection for finite-state Markov channel and propose a Q-learning assisted relay selection scheme. Specifically, we firstly analyze the achievable effective secrecy throughput of random selection scheme and optimal selection scheme, respectively, showing that the secrecy performance is highly determined by relay selection methodology. Then, we leverage the Q-learning to learn how to select relay for finite-state Markov channel, which is capable of selecting proper relay with outdated channel state information. Numerical results demonstrate that our proposed Q-learning assisted relay selection scheme can achieve a significant improvement of effective secrecy throughput even with outdated channel information.

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U2 - 10.1109/VTC2021-Spring51267.2021.9448708

DO - 10.1109/VTC2021-Spring51267.2021.9448708

M3 - Conference contribution

AN - SCOPUS:85112433967

T3 - IEEE Vehicular Technology Conference

BT - 2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring

Y2 - 25 April 2021 through 28 April 2021

ER -

Learning-Assisted Secure Relay Selection with Outdated CSI for Finite-State Markov Channel

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