AI-Driven Resource Allocation in Optical Wireless Communication Systems
Author:
Affiliation:
1. University of Leeds,School of Electronics and Electrical Engineering,Leeds,UK,LS2 9JT
2. Umm Al-Qura University,Department of Computer Engineering,Makkah,Saudi Arabia
3. Kings’ College London,Department of Engineering,London,United Kingdom
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10207167/10207171/10207473.pdf?arnumber=10207473
Reference29 articles.
1. Cooperative artificial neural networks for rate-maximization in optical wireless networks;qidan;Proc ICC 2023 - IEEE International Conference on Communications,2023
2. Artificial Neural Network for Resource Allocation in Laser-based Optical wireless Networks
3. Fast and Efficient Adaptation Algorithms for Multi-Gigabit Wireless Infrared Systems
4. User-centric cell formation for blind interference alignment in optical wireless networks;adnan-qidan;Proc ICC 2021 - IEEE International Conference on Communications,2021
5. Resource Allocation in User-Centric Optical Wireless Cellular Networks Based on Blind Interference Alignment
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