Joint user association and green energy allocation in HetNets with hybrid energy sources

In the heterogeneous networks (HetNets) powered by hybrid energy sources, it is imperative to reduce the total on-grid energy consumption as well as minimize the peak-to-average on-grid energy consumption ratio, since the large peak-to-average on-grid energy consumption ratio will translate into the high operational expenditure (OPEX) for mobile network operators. In this paper, we propose a joint user association and green energy allocation algorithm which aims to lexicographically minimize the on-grid energy consumption in HetNets, where all the base stations (BSs) are assumed to be powered by both the power grid and renewable energy sources. The optimization problem involves both the user association optimization in space dimension, and the green energy allocation in time dimension. The independence nature of this two-dimensional optimization allows us to decompose the problem into two sub-problems. We first formulate the user association optimization in space dimension as a convex optimization problem to minimize total energy consumption via balancing the traffic across different BSs in a certain time slot. We then optimize the green energy allocation across different time slots for an individual BS to lexicographically minimize the on-grid energy consumption. Simulation results indicate the proposed algorithm achieves significant on-grid energy saving, and substantially reduces peak-to-average on-grid energy consumption ratio.

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

[2]  Jean-Yves Le Boudec,et al.  A Unified Framework for Max-Min and Min-Max Fairness With Applications , 2007, IEEE/ACM Transactions on Networking.

[3]  Tiankui Zhang,et al.  Optimal user association for delay-power tradeoffs in HetNets with hybrid energy sources , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).

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

[5]  Slawomir Stanczak,et al.  Planning of Cellular Networks Enhanced by Energy Harvesting , 2013, IEEE Communications Letters.

[6]  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.

[7]  Zhisheng Niu,et al.  Optimal Power Allocation for Energy Harvesting and Power Grid Coexisting Wireless Communication Systems , 2013, IEEE Transactions on Communications.

[8]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station , 2013, IEEE Transactions on Wireless Communications.

[9]  Yueping Wu,et al.  Delay-Aware BS Discontinuous Transmission Control and User Scheduling for Energy Harvesting Downlink Coordinated MIMO Systems , 2012, IEEE Transactions on Signal Processing.

[10]  G. Fettweis,et al.  ICT ENERGY CONSUMPTION – TRENDS AND CHALLENGES , 2008 .

[11]  Haiyun Luo,et al.  Traffic-driven power saving in operational 3G cellular networks , 2011, MobiCom.

[12]  Minoru Etoh,et al.  Energy Consumption Issues on Mobile Network Systems , 2008, 2008 International Symposium on Applications and the Internet.

[13]  Nirwan Ansari,et al.  On Optimizing Green Energy Utilization for Cellular Networks with Hybrid Energy Supplies , 2013, IEEE Transactions on Wireless Communications.