Energy and Throughput Trade-Offs in Cellular Networks Using Base Station Switching

Base station operation consumes a lot of energy, a considerable amount of which can be saved by switching off base stations during low user demand (for example, at night). Base station switching (BSS) can result in loss in coverage if not performed properly. We show that coverage is closely related to scheduling via power management and that the bottleneck is typically the uplink. To save energy, we propose a set of BSS patterns, at a global system-level, that have the potential to provide full coverage if the appropriate schedulers are used. We further show that the existing benchmark uplink scheduling schemes do not provide full coverage when BSS is used in urban as well as rural macro-cell environments (the downlink benchmark scheduling scheme provides full coverage only for some of the BSS patterns). Hence, we propose novel scheduling schemes for both uplink and downlink that realistically model interference, ensure full coverage, and provide good energy-performance trade-offs for the proposed BSS patterns. We also present a low complexity high performance heuristic for the proposed uplink scheduler. Finally, we show the presented models and results can be used to quantify, offline, the energy-performance trade-offs under different operating scenarios.

[1]  Yang Richard Yang,et al.  Proportional Fairness in Multi-Rate Wireless LANs , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[2]  Vasilis Friderikos,et al.  Energy-Efficient Relaying via Store-Carry and Forward within the Cell , 2014, IEEE Transactions on Mobile Computing.

[3]  Byeong Gi Lee,et al.  A Joint Algorithm for Base Station Operation and User Association in Heterogeneous Networks , 2013, IEEE Communications Letters.

[4]  Hervé Rivano,et al.  Optimization method for the joint allocation of modulation schemes, coding rates, resource blocks and power in self-organizing LTE networks , 2011, 2011 Proceedings IEEE INFOCOM.

[5]  Rajasekhar Sappidi,et al.  Planning for small cells in a cellular network: Why it is worth it , 2014, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[6]  Wanjiun Liao,et al.  On Optimal Cell Activation for Coverage Preservation in Green Cellular Networks , 2014, IEEE Transactions on Mobile Computing.

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

[8]  Abbas Jamalipour,et al.  Distributed Inter-BS Cooperation Aided Energy Efficient Load Balancing for Cellular Networks , 2013, IEEE Transactions on Wireless Communications.

[9]  L. Chiaraviglio,et al.  Optimal Energy Savings in Cellular Access Networks , 2009, 2009 IEEE International Conference on Communications Workshops.

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

[11]  Jing Xu,et al.  Energy-Efficient Coordinated Scheduling Mechanism for Cellular Communication Systems with Multiple Component Carriers , 2013, IEEE Journal on Selected Areas in Communications.

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

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

[14]  Bhaskar Krishnamachari,et al.  Toward Energy-Efficient Operation of Base Stations in Cellular Wireless Networks , 2012 .

[15]  Geoffrey Ye Li,et al.  Fundamental trade-offs on green wireless networks , 2011, IEEE Communications Magazine.

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

[17]  Muhammad Ali Imran,et al.  How much energy is needed to run a wireless network? , 2011, IEEE Wireless Communications.