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2021 Volume 8
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ARTICLE   Open Access    

Optimal Wireless Information and Power Transfer Using Deep Q-Network

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  • In this paper, a multiantenna wireless transmitter communicates with an information receiver while radiating RF energy to surrounding energy harvesters. The channel between the transceivers is known to the transmitter, but the channels between the transmitter and the energy harvesters are unknown to the transmitter. By designing its transmit covariance matrix, the transmitter fully charges the energy buffers of all energy harvesters in the shortest amount of time while maintaining the target information rate toward the receiver. At the beginning of each time slot, the transmitter determines the particular beam pattern to transmit with. Throughout the whole charging process, the transmitter does not estimate the energy harvesting channel vectors. Due to the high complexity of the system, we propose a novel deep Q-network algorithm to determine the optimal transmission strategy for complex systems. Simulation results show that deep Q-network is superior to the existing algorithms in terms of the time consumption to fulfill the wireless charging process.
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    Xing Y, Pan H, Xu B, Tapparello C, Shi W, et al. 2021. Optimal Wireless Information and Power Transfer Using Deep Q-Network. Wireless Power Transfer 8: 5513509 doi: 10.1155/2021/5513509
    Xing Y, Pan H, Xu B, Tapparello C, Shi W, et al. 2021. Optimal Wireless Information and Power Transfer Using Deep Q-Network. Wireless Power Transfer 8: 5513509 doi: 10.1155/2021/5513509

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ARTICLE   Open Access    

Optimal Wireless Information and Power Transfer Using Deep Q-Network

Wireless Power Transfer  8 Article number: 10.1155/2021/5513509  (2021)  |  Cite this article

Abstract: In this paper, a multiantenna wireless transmitter communicates with an information receiver while radiating RF energy to surrounding energy harvesters. The channel between the transceivers is known to the transmitter, but the channels between the transmitter and the energy harvesters are unknown to the transmitter. By designing its transmit covariance matrix, the transmitter fully charges the energy buffers of all energy harvesters in the shortest amount of time while maintaining the target information rate toward the receiver. At the beginning of each time slot, the transmitter determines the particular beam pattern to transmit with. Throughout the whole charging process, the transmitter does not estimate the energy harvesting channel vectors. Due to the high complexity of the system, we propose a novel deep Q-network algorithm to determine the optimal transmission strategy for complex systems. Simulation results show that deep Q-network is superior to the existing algorithms in terms of the time consumption to fulfill the wireless charging process.

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    Cite this article
    Xing Y, Pan H, Xu B, Tapparello C, Shi W, et al. 2021. Optimal Wireless Information and Power Transfer Using Deep Q-Network. Wireless Power Transfer 8: 5513509 doi: 10.1155/2021/5513509
    Xing Y, Pan H, Xu B, Tapparello C, Shi W, et al. 2021. Optimal Wireless Information and Power Transfer Using Deep Q-Network. Wireless Power Transfer 8: 5513509 doi: 10.1155/2021/5513509

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