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Volume 43 Issue 5
May  2021
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Weijia LEI, Anqi FU, Hongjiang LEI, Xianzhong XIE. Online Power Control Algorithm for Secure Relay Transmission Network with Energy Harvesting[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1306-1314. doi: 10.11999/JEIT200104
Citation: Weijia LEI, Anqi FU, Hongjiang LEI, Xianzhong XIE. Online Power Control Algorithm for Secure Relay Transmission Network with Energy Harvesting[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1306-1314. doi: 10.11999/JEIT200104

Online Power Control Algorithm for Secure Relay Transmission Network with Energy Harvesting

doi: 10.11999/JEIT200104
Funds:  The National Natural Science Foundation of China (61971080, 61471076), The Key Project of Science and Technology Research of Chongqing Education Commission (KJZD-K201800603, KJZD-M201900602), The Open Fund of the Shaanxi Key Laboratory of Information Communication Network and Security (ICNS201807)
  • Received Date: 2020-02-14
  • Rev Recd Date: 2020-11-27
  • Available Online: 2020-12-05
  • Publish Date: 2021-05-18
  • For amplify-and-forward relay networks where both the source node and the relay node are powered by the harvested energy and the information for the two destination nodes are required to keep secrecy each other, an algorithm is proposed to maximize the long-term average secrecy rate by jointly optimizing the transmission power of the source node and the relay node. Since the energy arrivals and channel states are stochastic processes, the problem is a stochastic optimization problem. The Lyapunov optimization framework is used to transform the long-term optimization problem into a “virtual queue drift plus penalty” minimization problem per time slot under the constraints of battery operation and energy using. The transformed optimization problem is solved. The simulation results show that the proposed algorithm has significant advantages over the comparison algorithms in the long-term average secrecy rate. Furthermore, the proposed algorithm only depends on the current battery state and channel state to make the decision, which is a practical and low-complexity algorithm.
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