4.7 Article

Learning-Based Joint Optimization of Transmit Power and Harvesting Time in Wireless-Powered Networks With Co-Channel Interference

期刊

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 69, 期 3, 页码 3500-3504

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.2972596

关键词

Neural network; energy efficiency; energy harvesting; time switching; optimization

资金

  1. National Research Foundation of Korea (NRF) - Korea government (MSIT) [2019R1A2C4070466, 2019R1F1A1058587]
  2. National Research Foundation of Korea [22A20152213084, 2019R1A2C4070466, 2019R1F1A1058587] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

In this paper, we consider a wireless-powered network with co-channel interference where the transmitters control their transmit power and receivers harvest wireless energy using a time switching policy. Considering the interference channels among multiple nodes, we jointly optimize the transmit power and energy harvesting time to maximize the energy efficiency of the network. To solve this non-convex optimization problem, we first design an iterative algorithm based on a typical optimization technique, and then, propose a learning algorithm based on a neural network with a proper loss function. Simulation results show that the proposed learning algorithm can achieve a near-optimal energy efficiency with reducing the computational complexity, compared to an iterative algorithm with a suboptimal performance.

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