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Deep Q Network for Wiretap Channel Model with Energy Harvesting

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Communications and Networking (ChinaCom 2019)

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Abstract

An energy harvesting wiretap channel model is considered in which the sender is an energy harvesting node. It is assumed that at each time slot only information about the current state of the sending node is available. In order to find an effective power allocation strategy to maximize secrecy rate, we put forward a deep Q network (DQN) scheme. First, we analyze the constraints of the system and the issue of maximizing the secrecy rate. Next, the power allocation problem is formulated as a Markov Decision Process (MDP) with unknown transition probabilities. In order to solve the continuous state space problem that traditional Q learning algorithms cannot handle, we apply neural networks to approximate the value function. Finally, an online joint resource power allocation algorithm based on DQN is presented. Simulation results show that the proposed algorithm can effectively improve the secrecy rate of the model.

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Acknowledgement

This paper is sponsored by the National Nature Science Foundation of China (61971080, 61471076); Chongqing Basic Research and Frontier Exploration Project (cstc2018jcyjAX0432, cstc2017jcyjAX0204); The Key Project of Science and Technology Research of Chongqing Education Commission (KJZD-K201800603).

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Authors and Affiliations

  1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

    Zhaohui Li & Weijia Lei

Authors
  1. Zhaohui Li
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  2. Weijia Lei
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Correspondence to Zhaohui Li .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. School of Computer Software, Tianjin University, Tianjin, China

    Zhiyong Feng

  3. Hangzhou Dianzi University, Hangzhou, China

    Jun Yu

  4. Tongji University, Shanghai Shi, China

    Jun Wu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, Z., Lei, W. (2020). Deep Q Network for Wiretap Channel Model with Energy Harvesting. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_32

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  • DOI: https://doi.org/10.1007/978-3-030-41114-5_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41113-8

  • Online ISBN: 978-3-030-41114-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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