Model Predictive Cell Zooming for Energy-Harvesting Small Cell Networks

This paper addresses the real-time control of transmission power for small cell base stations (SBSs) exploiting energy- harvesting sources. We employ model predictive control and optimize an objective function that contains the number of users with a given quality of experience and the average state of charge. We first determine the number of active SBSs in the viewpoint of energy efficiency and then approximate the objective function. Finally, we illustrate the proposed method through a numerical example, comparing it with a static method based on statistical information.

[1]  Nei Kato,et al.  QoE-Guaranteed and Power-Efficient Network Operation for Cloud Radio Access Network With Power Over Fiber , 2015, IEEE Transactions on Computational Social Systems.

[2]  Francesco Borrelli,et al.  MPC-Based Approach to Active Steering for Autonomous Vehicle Systems , 2005 .

[3]  Panagiotis D. Christofides,et al.  Distributed model predictive control: A tutorial review and future research directions , 2013, Comput. Chem. Eng..

[4]  Yun Li,et al.  PID control system analysis, design, and technology , 2005, IEEE Transactions on Control Systems Technology.

[5]  Khaled Ben Letaief,et al.  Energy harvesting small cell networks: feasibility, deployment, and operation , 2015, IEEE Communications Magazine.

[6]  Xuemin Shen,et al.  Energy-Aware Traffic Offloading for Green Heterogeneous Networks , 2016, IEEE Journal on Selected Areas in Communications.

[7]  Jing Yang,et al.  Optimal Packet Scheduling in an Energy Harvesting Communication System , 2010, IEEE Transactions on Communications.

[8]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station , 2013, IEEE Transactions on Wireless Communications.

[9]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[10]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[11]  Zhisheng Niu,et al.  Toward dynamic energy-efficient operation of cellular network infrastructure , 2011, IEEE Communications Magazine.

[12]  Carlos E. T. Dorea,et al.  Design and Implementation of Model-Predictive Control With Friction Compensation on an Omnidirectional Mobile Robot , 2014, IEEE/ASME Transactions on Mechatronics.

[13]  Zhisheng Niu,et al.  Cell zooming for cost-efficient green cellular networks , 2010, IEEE Communications Magazine.

[14]  Nei Kato,et al.  QoE-Guaranteed and Sustainable User Position Guidance for Post-Disaster Cloud Radio Access Network , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[15]  Huibert Kwakernaak,et al.  H2-optimization - Theory and applications to robust control design , 2000, Annu. Rev. Control..

[16]  Giuseppe Piro,et al.  HetNets Powered by Renewable Energy Sources: Sustainable Next-Generation Cellular Networks , 2013, IEEE Internet Computing.