Optimizing Simultaneous Lightwave Information and Power Transfer Under Practical Indoor Mobility With Reinforcement Learning

Optimizing Simultaneous Lightwave Information and Power Transfer Under Practical Indoor Mobility With Reinforcement Learning

This article investigates reinforcement learning (RL)-based solutions for optimizing resource allocations in simultaneous lightwave information and power transfer (SLIPT) under practical indoor mobility. Encountering the challenges of excessive outages and intermittent channels posed by practical mo...

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Bibliographic Details
Main Authors: Zi-Yang Wu, Zhi-Shi Chen, Peng-Cheng Song
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Photonics Journal
Subjects:
Deep deterministic policy gradient (DDPG)
energy harvesting
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reinforcement learning (RL)
simultaneous lightwave information and power transfer (SLIPT)
simultaneous wireless information and power transfer (SWIPT)
Online Access:https://ieeexplore.ieee.org/document/10226257/
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