TY - GEN
T1 - Q-learning algorithm for resource allocation in WDMA-based optical wireless communication networks
AU - Elgamal, Abdelrahman S.
AU - Alsulami, Osama Z.
AU - Qidan, Ahmad Adnan
AU - El-Gorashi, Taisir E.H.
AU - Elmirghani, Jaafar M.H.
N1 - Funding Information:
ACKNOWLEDGMENTS This work has been supported in part by the Engineering and Physical Sciences Research Council (EPSRC), in part by the INTERNET project under Grant EP/H040536/1, and in part by the STAR project under Grant EP/K016873/1 and in part by the TOWS project under Grant EP/S016570/1. All data are provided in full in the results section of this paper. ASE would like to acknowledge EPSRC for funding his PhD scholarship. OZA would like to thank Umm Al-Qura University in the Kingdom of Saudi Arabia for funding his PhD scholarship.
Publisher Copyright:
© 2021 University of Split, FESB.
PY - 2021/9/8
Y1 - 2021/9/8
N2 - Visible Light Communication (VLC) has been widely investigated during the last decade due to its ability to provide high data rates with low power consumption. In general, resource management is an important issue in cellular networks that can highly effect their performance. In this paper, an optimisation problem is formulated to assign each user to an optimal access point and a wavelength at a given time. This problem can be solved using mixed integer linear programming (MILP). However, using MILP is not considered a practical solution due to its complexity and memory requirements. In addition, accurate information must be provided to perform the resource allocation. Therefore, the optimisation problem is reformulated using reinforcement learning (RL), which has recently received tremendous interest due to its ability to interact with any environment without prior knowledge. In this paper, the resource allocation optimisation problem in VLC systems is investigated using the basic Q-learning algorithm. Two scenarios are simulated to compare the results with the previously proposed MILP model. The results demonstrate the ability of the Q-learning algorithm to provide optimal solutions close to the MILP model without prior knowledge of the system.
AB - Visible Light Communication (VLC) has been widely investigated during the last decade due to its ability to provide high data rates with low power consumption. In general, resource management is an important issue in cellular networks that can highly effect their performance. In this paper, an optimisation problem is formulated to assign each user to an optimal access point and a wavelength at a given time. This problem can be solved using mixed integer linear programming (MILP). However, using MILP is not considered a practical solution due to its complexity and memory requirements. In addition, accurate information must be provided to perform the resource allocation. Therefore, the optimisation problem is reformulated using reinforcement learning (RL), which has recently received tremendous interest due to its ability to interact with any environment without prior knowledge. In this paper, the resource allocation optimisation problem in VLC systems is investigated using the basic Q-learning algorithm. Two scenarios are simulated to compare the results with the previously proposed MILP model. The results demonstrate the ability of the Q-learning algorithm to provide optimal solutions close to the MILP model without prior knowledge of the system.
KW - MILP
KW - Reinforcement learning
KW - Resource allocation
KW - Visible light communication
UR - http://www.scopus.com/inward/record.url?scp=85118465735&partnerID=8YFLogxK
UR - https://2021.splitech.org/call-for-papers/
U2 - 10.23919/SpliTech52315.2021.9566383
DO - 10.23919/SpliTech52315.2021.9566383
M3 - Conference contribution
AN - SCOPUS:85118465735
SN - 9781665442022
T3 - 2021 6th International Conference on Smart and Sustainable Technologies, SpliTech 2021
SP - 1
EP - 5
BT - 2021 6th International Conference on Smart and Sustainable Technologies, SpliTech 2021
A2 - Solic, Petar
A2 - Nizetic, Sandro
A2 - Rodrigues, Joel J. P. C.
A2 - Rodrigues, Joel J.P.C.
A2 - Gonzalez-de-Artaza, Diego Lopez-de-Ipina
A2 - Perkovic, Toni
A2 - Catarinucci, Luca
A2 - Patrono, Luigi
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - United States
T2 - 6th International Conference on Smart and Sustainable Technologies, SpliTech 2021
Y2 - 8 September 2021 through 11 September 2021
ER -
