KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Energy-Saving Oriented On/Off Strategies in Heterogeneous Networks : an Asynchronous Approach with Dynamic Traffic Variations

  • Tang, Lun (Key Laboratory of Mobile Communication, Chongqing University of Posts and Telecommunications) ;
  • Wang, Weili (Key Laboratory of Mobile Communication, Chongqing University of Posts and Telecommunications) ;
  • Chen, Qianbin (Key Laboratory of Mobile Communication, Chongqing University of Posts and Telecommunications)
  • Received : 2017.12.04
  • Accepted : 2018.05.16
  • Published : 2018.11.30
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Abstract

Recent works have validated the possibility of reducing the energy consumption in wireless heterogeneous networks, achieved by switching on/off some base stations (BSs) dynamically. In this paper, to realize energy conservation, the discrete time Markov Decision Process (DTMDP) is developed to match up the BS switching operations with the traffic load variations. Then, an asynchronous decision-making algorithm, which is based on the Bellman equation and the on/off priorities of the BSs, is firstly put forward and proved to be optimal in this paper. Through reducing the state and action space during one decision, the proposed asynchronous algorithm can avoid the "curse of dimensionality" occurred in DTMDP frequently. Finally, numerical simulations are conducted to validate the effectiveness and advantages of the proposed asynchronous on/off strategies.

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References

  1. H. Zhang, A. Gladisch, M. Pickavet, Z. Tao and W. Mohr, "Energy efficiency in communications," IEEE Commun. Mag., vol. 48, no. 11, pp. 48-49, 2010. https://doi.org/10.1109/MCOM.2010.5621966
  2. Z. Niu, "TANGO: traffic-aware network planning and green operation," IEEE Wireless Commun., vol. 18, no. 5, pp. 25-29, 2011. https://doi.org/10.1109/MWC.2011.6056689
  3. AA. Abdulkafi, TS. Kiong and IK. Sileh, "A Survey of Energy Efficiency Optimization in Heterogeneous Cellular Networks," Ksii Transactions on Internet & Information Systems, vol. 10, no. 2, pp. 462-483, 2016. https://doi.org/10.3837/tiis.2016.02.002
  4. H. Gao, W. Ejaz and M.Jo, "Cooperative Wireless Energy Harvesting and Spectrum Sharing in 5G Networks," IEEE Access, pp.3647-3658, 2017.
  5. H. Gao, Y. Du and C. Li, "Quantum fireworks algorithm for optimal cooperation mechanism of energy harvesting cognitive radio," Journal of Systems Engineering and Electronics, vol. 29, no. 1, pp.18-30, 2018. https://doi.org/10.21629/JSEE.2018.01.02
  6. J. Zhang, Q. Zhou, D. W. K. Ng and M. Jo, "Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks," Sensors, vol.17, no. 9, 2125, 2017. https://doi.org/10.3390/s17092125
  7. Q. Wang and J. Zheng, "A Distributed base station On/Off Control Mechanism for energy efficiency of small cell networks," in Proc. of IEEE Int. Conf. Commun. (ICC), pp. 3317-3322, 2015.
  8. N. Yu, Y. Miao and L. Mu, "Minimizing Energy Cost by Dynamic Switching ON/OFF Base Stations in Cellular Networks," IEEE Trans. Wireless Commun., vol. 15, no. 11, pp. 7457-7469, 2016. https://doi.org/10.1109/TWC.2016.2602824
  9. G. Su, B. Chen and X. Lin, "User association and base station sleep management in dense heterogeneous cellular networks.," Ksii Transactions on Internet & Information Systems, vol. 11, no.4, pp. 2058-2074, 2017. https://doi.org/10.3837/tiis.2017.04.013
  10. J. Kim, P.Y. Kong, N.O. Song, J.K.K. Rhee and S. Al-Araji, "MDP Based Dynamic Base Station Management for Power Conservation in Self-Organizing Networks," in Proc. of IEEE Wireless Comm. and Networking Conf. (WCNC), pp. 2561-2567, 2014.
  11. E. Oh, K. Son and B. Krishnamachari, "Dynamic Base Station Switching-On/Off Strategies for Green Cellular Networks," IEEE Trans. Wireless Commun., vol. 12, no. 5, pp. 2126-2136, 2013. https://doi.org/10.1109/TWC.2013.032013.120494
  12. S. Samarakoon, M. Bennis and W. Saad, "Dynamic Clustering and on / off Strategies for Wireless Small Cell Networks," IEEE Trans. Wireless Commun., vol. 15, no. 3, pp. 2164-2178, 2015. https://doi.org/10.1109/TWC.2015.2499182
  13. Y. Yang, L. Chen and W. Dong, "Active Base Station Set Optimization for Minimal Energy Consumption in Green Cellular Networks," IEEE Trans. Veh. Technol., 2015, vol. 64, no. 11, pp. 5340-5349, 2015. https://doi.org/10.1109/TVT.2014.2385313
  14. L. Tang, W.Wang, Y.Wang and Q. Chen, "An energy-saving algorithm with joint user association, clustering and on/off strategies in dense heterogeneous networks," IEEE Access, pp.12988-13000, 2017.
  15. L. Sakar, L. E. Elayoubi, R. Combes and T. Chahed, "Optimal Control of Wake Up Mechanisms of Femtocells in Heterogeneous Networks," IEEE J. Sel. Areas Commun., vol. 30, no. 3, pp.664-672, 2012. https://doi.org/10.1109/JSAC.2012.120415
  16. R. Li, Z. Zhao, X. Chen, J. Palicot and H. Zhang, ''TACT: A transfer actor-critic learning framework for energy saving in cellular radio access networks,'' IEEE Trans. Wireless Commun., vol. 13, no. 4, pp. 2000-2011, 2014. https://doi.org/10.1109/TWC.2014.022014.130840
  17. X. Chen, J. Wu, Y. Cai, H. Zhang and T. Chen, "Energy-efficiency oriented traffic offloading in wireless networks: a brief survey and a learning approach for heterogeneous cellular networks," IEEE J. Sel. Areas Commun., vol. 33, no. 4, 627-640, 2015. https://doi.org/10.1109/JSAC.2015.2393496
  18. P.Y. Kong, "Optimal probabilistic policy for dynamic resource activation using markov decision process in green wireless networks," IEEE Trans. Mobile Comput., vol. 13, no.10, pp. 2357-2368, 2014. https://doi.org/10.1109/TMC.2014.2307328
  19. R. Sutton and A. Barto, Reinforcement Learning: An Introduction. Cambridge University Press, 1998.