Self-Adaptive Scheduling of Base Transceiver Stations in Green 5G Networks

In this paper, we design self-adaptive scheduling (SAS) algorithms for base transceiver stations (BTSs) of 5G networks to improve energy efficiency, reduce carbon footprint, and develop a self-sustainable green cellular network. In the SAS algorithm, a BTS switches among its operating states (active, turned-off, and sleep), thereby exploiting the traffic loads of the BTS and the single-hop neighbor BTSs thereof. The dynamic settings of traffic thresholds help the SAS system in achieving a high degree of cooperation among the neighborhood BTSs, which in turn increases the energy savings of the network. Each active SAS BTS independently and dynamically decides in determining its operation state, thus make our proposed SAS algorithms fully distributed. Results from a simulation conducted in network simulator version 3 show that BTS scheduling significantly influences cellular networks, and the proposed SAS algorithm can significantly increase the energy savings compared with state-of-the-art protocols.

[1]  Zhangdui Zhong,et al.  A dynamic energy-saving strategy for green cellular railway communication network , 2015, EURASIP J. Wirel. Commun. Netw..

[2]  Kyung Sup Kwak,et al.  Inter-cell cooperation aided dynamic base station switching for energy efficient cellular networks , 2012, 2012 18th Asia-Pacific Conference on Communications (APCC).

[3]  Bhaskar Krishnamachari,et al.  Dynamic Base Station Switching-On/Off Strategies for Green Cellular Networks , 2013, IEEE Transactions on Wireless Communications.

[4]  Mahesh K. Marina,et al.  Network Slicing in 5G: Survey and Challenges , 2017, IEEE Communications Magazine.

[5]  Biljana Badic,et al.  Energy Efficient Radio Access Architectures for Green Radio: Large versus Small Cell Size Deployment , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

[6]  Amit Kumar Das,et al.  A distributed wake-up scheduling algorithm for base stations in green cellular networks , 2012, ICUIMC '12.

[7]  J.T. Louhi,et al.  Energy efficiency of modern cellular base stations , 2007, INTELEC 07 - 29th International Telecommunications Energy Conference.

[8]  Jing Wang,et al.  Green 5G Heterogeneous Networks Through Dynamic Small-Cell Operation , 2016, IEEE Journal on Selected Areas in Communications.

[9]  Xianfu Chen,et al.  Optimal Base Station Sleeping in Green Cellular Networks: A Distributed Cooperative Framework Based on Game Theory , 2015, IEEE Transactions on Wireless Communications.

[10]  Majid Ghaderi,et al.  Energy cost reduction in cellular networks through dynamic base station activation , 2014, 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).

[11]  Sunil Keshavji Vadgama,et al.  Trends in Green Wireless Access , 2009 .

[12]  Weisi Guo,et al.  Dynamic Cell Expansion with Self-Organizing Cooperation , 2013, IEEE Journal on Selected Areas in Communications.

[13]  Marceau Coupechoux,et al.  Limiting Power Transmission of Green Cellular Networks: Impact on Coverage and Capacity , 2010, IEEE International Conference on Communications.

[14]  Tiankui Zhang,et al.  QoS-aware user association based on cell zooming for energy efficiency in cellular networks , 2013, 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops).

[15]  Moshe Zukerman,et al.  Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey , 2015, IEEE Communications Surveys & Tutorials.

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

[17]  Albrecht J. Fehske,et al.  Energy Efficiency Improvements through Micro Sites in Cellular Mobile Radio Networks , 2009, 2009 IEEE Globecom Workshops.

[18]  Jin Chen,et al.  Toward 5G: A Novel Sleeping Strategy for Green Distributed Base Stations in Small Cell Networks , 2016, 2016 12th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN).

[19]  Marco Ajmone Marsan,et al.  Energy efficient management of two cellular access networks , 2010, PERV.

[20]  Lajos Hanzo,et al.  Green radio: radio techniques to enable energy-efficient wireless networks , 2011, IEEE Communications Magazine.

[21]  陈建亚,et al.  Dynamic Sleeping Algorithm of Base Station Based on Spatial Features , 2014 .

[22]  Zhisheng Niu,et al.  TANGO: traffic-aware network planning and green operation , 2011, IEEE Wireless Communications.

[23]  Geoffrey Ye Li,et al.  An Overview of Sustainable Green 5G Networks , 2016, IEEE Wireless Communications.

[24]  Matti Latva-aho,et al.  Opportunistic sleep mode strategies in wireless small cell networks , 2014, 2014 IEEE International Conference on Communications (ICC).

[25]  Yuan Yuan,et al.  A QoE-orientated base station sleeping strategy for multi-services in cellular networks , 2015, 2015 International Conference on Wireless Communications & Signal Processing (WCSP).

[26]  Abbas Jamalipour,et al.  An eco-inspired energy efficient access network architecture for next generation cellular systems , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[27]  Vincenzo Mancuso,et al.  Reducing costs and pollution in cellular networks , 2011, IEEE Communications Magazine.

[28]  Fang Chen,et al.  Dynamic sleep control in green relay-assisted networks for energy saving and QoS improving , 2015, 2015 IEEE/CIC International Conference on Communications in China (ICCC).

[29]  Gerhard Fettweis,et al.  The global footprint of mobile communications: The ecological and economic perspective , 2011, IEEE Communications Magazine.

[30]  Ness B. Shroff,et al.  Dynamic user association and energy control in cellular networks with renewable resources , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[31]  Federico Boccardi,et al.  SLEEP mode techniques for small cell deployments , 2011, IEEE Communications Magazine.

[32]  Jang-Won Lee,et al.  Energy and traffic aware dynamic topology management for wireless cellular networks , 2012, 2012 IEEE International Conference on Communication Systems (ICCS).

[33]  Marco Ajmone Marsan,et al.  Energy-efficient management of UMTS access networks , 2009, 2009 21st International Teletraffic Congress.

[34]  Vasilis Friderikos,et al.  Switching off low utilization base stations via store carry and forward relaying , 2010, 2010 IEEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications Workshops.

[35]  Vijay K. Bhargava,et al.  Green Cellular Networks: A Survey, Some Research Issues and Challenges , 2011, IEEE Communications Surveys & Tutorials.

[36]  Gerhard Fettweis,et al.  Energy Efficiency Aspects of Base Station Deployment Strategies for Cellular Networks , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

[37]  Tijani Chahed,et al.  Minimizing Energy Consumption via Sleep Mode in Green Base Station , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[38]  Abbas Jamalipour,et al.  A protocooperation-based sleep-wake architecture for next generation green cellular access networks , 2010, 2010 4th International Conference on Signal Processing and Communication Systems.

[39]  Poul E. Heegaard.  Empirical Observations of Traffic Patterns in Mobile and IP Telephony , 2007, NEW2AN.