Joint Cell Activation and User Association for Backhaul Load Balancing in Green HetNets

This letter proposes a joint cell activation and user association scheme to address the power consumption and backhaul load balancing issues in green dense heterogeneous networks (HetNets). In this scheme, an optimization problem is formulated for jointly minimizing power consumption and optimizing...

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Bibliographic Details
Published in:IEEE wireless communications letters 2020-09, Vol.9 (9), p.1486-1490
Main Authors: Lee, Ying Loong, Tan, Wei Lun, Lau, Simon Boung Yew, Chuah, Teong Chee, El-Saleh, Ayman A., Qin, Donghong
Format: Article
Language:English
Subjects:
Activation
Algorithms
backhaul load balancing
Cell activation
Convex functions
Electronic mail
HetNets
Linear programming
Load balancing
Load management
Machine learning
Optimization
Power consumption
Power demand
Quality of service
user association
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Summary:This letter proposes a joint cell activation and user association scheme to address the power consumption and backhaul load balancing issues in green dense heterogeneous networks (HetNets). In this scheme, an optimization problem is formulated for jointly minimizing power consumption and optimizing backhaul load balance of dense HetNets, subject to diverse quality of service (QoS) requirements and heterogeneous backhaul capacities. To solve this problem, a Q-learning-based algorithm is developed. Results show that the proposed scheme achieves substantial performance improvements over several baseline schemes in terms of fairness, QoS and energy efficiency.
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2020.2994643