• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Reinforcement Learning Framework for Autonomous Cell Activation and Customized Energy-Efficient Resource Allocation in C-RANs


Abstract

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.


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Cite this article

[IEEE Style]
G. Sun, G. O. Boateng, H. Huang and W. Jiang, "A Reinforcement Learning Framework for Autonomous Cell Activation and Customized Energy-Efficient Resource Allocation in C-RANs," KSII Transactions on Internet and Information Systems, vol. 13, no. 8, pp. 3821-3841, 2019. DOI: 10.3837/tiis.2019.08.001.

[ACM Style]
Guolin Sun, Gordon Owusu Boateng, Hu Huang, and Wei Jiang. 2019. A Reinforcement Learning Framework for Autonomous Cell Activation and Customized Energy-Efficient Resource Allocation in C-RANs. KSII Transactions on Internet and Information Systems, 13, 8, (2019), 3821-3841. DOI: 10.3837/tiis.2019.08.001.

[BibTeX Style]
@article{tiis:22170, title="A Reinforcement Learning Framework for Autonomous Cell Activation and Customized Energy-Efficient Resource Allocation in C-RANs", author="Guolin Sun and Gordon Owusu Boateng and Hu Huang and Wei Jiang and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2019.08.001}, volume={13}, number={8}, year="2019", month={August}, pages={3821-3841}}