Abstract
This letter investigates hybrid networks composed of a radio frequency (RF) access point (AP) and multiple visible light communication (VLC) APs. We consider mobile multi-homing users that can aggregate resources from both RF and VLC APs. In hybrid RF/VLC networks, RF channel gains vary faster than VLC channels due to small scale fading. By leveraging multi-agent Q-learning to interact with the dynamics of wireless environments, we develop an online two-timescale power allocation strategy that optimizes the transmit powers at the RF and VLC APs to ensure quality-of-service satisfaction. Simulation results demonstrate the effectiveness of the proposed Q-learning based strategy.
Original language | English |
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Article number | 8926487 |
Pages (from-to) | 443-447 |
Number of pages | 5 |
Journal | IEEE Wireless Communications Letters |
Volume | 9 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Apr 2020 |
Externally published | Yes |
Keywords
- hybrid networks
- optimization
- Q-learning
- reinforcement learning
- two-timescale
- Visible light communication