Joint power-delay minimization in 4G wireless networks

In this paper, we formulate an optimization problem that jointly minimizes the network power consumption and transmission delay in broadband wireless networks. Power saving is achieved by adjusting the operation mode of the network Base Stations (BSs) from high transmit power levels to low transmit levels or switched-off. Minimizing the transmission delay is achieved by selecting the best user association with the BSs. We study the case of a realistic Long Term Evolution (LTE) Network where the challenge is the high computational complexity necessary to obtain the optimal solution. Therefore, we propose a simulated annealing based heuristic algorithm for the power-delay minimization problem. The proposed heuristic aims to compute the transmit power level of the network BSs and associate users with these BSs in a way that jointly minimizes the total network power and the total network delay. The simulation results show that the proposed algorithm has a low computational complexity which makes it advantageous compared with the optimal scheme. Moreover, the heuristic algorithm performs close to optimally and outperforms the existing approaches in realistic 4G deployments.

[1]  Duc Truong Pham,et al.  Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks , 2011 .

[2]  Luis Alonso,et al.  "Green" distance-aware base station sleeping algorithm in LTE-Advanced , 2012, 2012 IEEE International Conference on Communications (ICC).

[3]  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).

[4]  Yan Chen,et al.  Energy efficient coverage planning in cellular networks with sleep mode , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

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

[6]  S. Elayoubi,et al.  Performance evaluation of frequency planning schemes in OFDMA-based networks , 2008 .

[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]  Bernard Cousin,et al.  Joint power-delay minimization in green wireless access networks , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[9]  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.

[10]  Bernard Cousin,et al.  Power-Delay Tradeoffs in Green Wireless Access Networks , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

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

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

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

[14]  Y. Jading,et al.  INFSO-ICT-247733 EARTH Deliverable D 2 . 3 Energy efficiency analysis of the reference systems , areas of improvements and target breakdown , 2012 .

[15]  Oleksandr Romanko,et al.  Normalization and Other Topics in Multi­Objective Optimization , 2006 .

[16]  K. J. Ray Liu,et al.  Energy-efficient cellular network operation via base station cooperation , 2012, 2012 IEEE International Conference on Communications (ICC).