Towards Energy Efficient and Quality of Service Aware Cell Zooming in 5G Wireless Networks

This paper presents an energy efficient and quality of service aware dynamic cell zooming algorithm for dense heterogeneous networks. The exponential growth of mobile data traffic would lead to dense deployment of small base stations and eventually higher energy consumption in Fifth Generation (5G) wireless networks. We formulate a dynamic cell zooming and base stations sleep optimization algorithm for dense heterogeneous networks as a Linear Programming (LP) problem in order to not only minimize the system power consumption but also to guarantee the quality of service to end user. This is possible by optimally zooming the coverage area of macro base stations and small cells based upon real time traffic conditions. We characterize the optimal as well as provide an approximate solution, which, however, performs very closely to the optimum. The extensive performance evaluation of our proposed dynamic cell zooming algorithm shows that our proposed algorithm can significantly decrease both system energy consumption and outage probability.

[1]  Cicek Cavdar,et al.  5GrEEn: Towards Green 5G mobile networks , 2013, 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[2]  Kenneth Stewart,et al.  Enabling technologies and architectures for 5G wireless , 2014, 2014 IEEE MTT-S International Microwave Symposium (IMS2014).

[3]  Khairi Ashour Hamdi,et al.  Trade-off between energy and area spectral efficiencies of cell zooming and BSs cooperation , 2014, 2014 5th International Conference on Intelligent and Advanced Systems (ICIAS).

[4]  Eitan Altman,et al.  Optimum and Equilibrium in Assignment Problems With Congestion: Mobile Terminals Association to Base Stations , 2013, IEEE Transactions on Automatic Control.

[5]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[6]  Long Bao Le QoS-aware BS switching and cell zooming design for OFDMA green cellular networks , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[7]  Kunagorn Kunavut,et al.  Performance evaluation of dynamic cell zooming algorithms in omni-directional and sector-based cells , 2014, 2014 11th International Joint Conference on Computer Science and Software Engineering (JCSSE).

[8]  A. Lozano,et al.  What Will 5 G Be ? , 2014 .

[9]  Marco Caretti,et al.  Energy Efficiency in LTE-Advanced Networks with Relay Nodes , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

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

[11]  Xiaohu You,et al.  Dynamic user association for energy minimization in macro-relay network , 2012, 2012 International Conference on Wireless Communications and Signal Processing (WCSP).

[12]  Xiaohu You,et al.  Total energy minimization through dynamic station-user connection in macro-relay network , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[13]  Geoffrey Ye Li,et al.  A survey of energy-efficient wireless communications , 2013, IEEE Communications Surveys & Tutorials.

[14]  Rose Qingyang Hu,et al.  An energy efficient and spectrum efficient wireless heterogeneous network framework for 5G systems , 2014, IEEE Communications Magazine.

[15]  Zhong Fan,et al.  Emerging technologies and research challenges for 5G wireless networks , 2014, IEEE Wireless Communications.