Power-Delay Tradeoffs in Green Wireless Access Networks

Targeting energy efficiency while meeting user Quality of Service (QoS) is one of the most challenging problems in green wireless networks. In this paper, we propose an optimization model based on finding a tradeoff between reducing the number of active radio cells and increasing the transmit power of base stations (BSs) to better serve all users in the system. The main contribution of the paper is the formulation of a multiobjective optimization problem that jointly minimizes the network power consumption and the sum of the network user transmission delay. Our proposed problem is solved using an exhaustive search algorithm to obtain the optimal solution. Solving the optimization problem at hand is very challenging due to the high computational complexity of the exhaustive search. Therefore, we run simulations in a small network to give insights into the optimal solution. Specifically, we study different cases by tuning the respective weights of the power and delay costs. This is a distinctive and important feature of our model allowing it to reflect various decision preferences. Regarding these preferences and under various spatial distribution of users, results show that our solution allows the optimal network configuration to be selected in terms of power consumption while guaranteeing minimal delay for all users in the network.

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

[2]  Jens Zander,et al.  Energy efficiency improvements through heterogeneous networks in diverse traffic distribution scenarios , 2011, 2011 6th International ICST Conference on Communications and Networking in China (CHINACOM).

[3]  Johanne Cohen,et al.  Individual vs. Global Radio Resource Management in a Hybrid Broadband Network , 2011, 2011 IEEE International Conference on Communications (ICC).

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

[5]  Martin Heusse,et al.  Performance anomaly of 802.11b , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[6]  Gang Shen,et al.  Energy Efficiency of Heterogeneous Cellular Network , 2010, 2010 IEEE 72nd Vehicular Technology Conference - Fall.

[7]  Bhaskar Krishnamachari,et al.  Base Station Operation and User Association Mechanisms for Energy-Delay Tradeoffs in Green Cellular Networks , 2011, IEEE Journal on Selected Areas in Communications.

[8]  Bhaskar Krishnamachari,et al.  Energy Savings through Dynamic Base Station Switching in Cellular Wireless Access Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[9]  Josip Lorincz,et al.  Energy savings in wireless access networks through optimized network management , 2010, IEEE 5th International Symposium on Wireless Pervasive Computing 2010.

[10]  Bo Han,et al.  Cellular Traffic Offloading through WiFi Networks , 2011, 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems.

[11]  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.

[12]  Kinda Khawam,et al.  Distributed heuristic algorithms for RAT selection in wireless heterogeneous networks , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).