Energy-Efficient Resource Allocation for Multi-Cell OFDM Networks

ABSTRACT

This paper studies the downlink energy-efficient resource allocation in multi-cell orthogonal frequency division multiple networks with different user distributions in each cell. A non-convex optimization problem is formulated to maximize the energy efficiency of the whole network, which takes the user distribution in each cell as a fairness weight and considers the circuit power consumption and minimum data rate requirement. The optimization problem in fractional form is transformed into an equivalent optimization problem in subtractive form using Dinkelbach method and an iterative algorithm is proposed, in which the subcarrier allocation and power allocation are implemented separately. Heuristic graph-based algorithm is first proposed to achieve the subcarrier allocation and dual decomposition method is adopted to derive the optimal power allocation strategy to maximize the energy efficiency. Simulation results show that the proposed iterative resource allocation algorithm can achieve the maximum energy efficiency in a few iterations and balance capacity between cells with different load conditions which is represented by the relative user density in this paper. Moreover, trade-off between energy-efficiency and network capacity is also unveiled.

Keywords:

• Dinkelbach method
• Energy efficiency
• Non-convex optimization
• Resource allocation
• User distribution

Additional information

Funding

This work is supported in part by the National Natural Science Foundation of China [grant number 61302081]; the State Major Science and Technology Special Projects [grant number 2013ZX03003005], [grant number 2013ZX03001025]; the National Key Technology Support Program [grant number 2012BAH41F03].

Notes on contributors

Deyu Yuan

Deyu Yuan is currently working toward the PhD degree with Beijing University of Posts and Telecommunications (BUPT), China. His research interests include energy-efficient resource management in OFDM wireless networks, cross-layer optimization in heterogeneous networks, and cognitive radio networks.

E-mail: [email protected]

Mei Song

Mei Song received the BE and ME degrees from Tianjin University, China. She is currently a professor in BUPT, China, and also the vice dean of electronic engineering department. Her current research interests include resource allocation and mobility management in heterogeneous and cognitive network, cooperative communications, and other advanced technology in future communications.

E-mail: [email protected]

Yinglei Teng

Yinglei Teng received the PhD degree in electrical engineering from BUPT, China in 2011. She is now working as an assistant professor in School of Electronic Engineering at BUPT. Her current research interests include multiuser MIMO (multiple-input multiple-output), cooperative diversity and cognitive radio network, and cross-layer design technology.

E-mail: [email protected]

Xiaojuan Wang

Xiaojuan Wang is currently working toward the PhD degree with BUPT, China. Her current research interests include resource management in heterogeneous networks, applications of stochastic geometry in wireless networks and cognitive radio.

E-mail: [email protected]

Xianmiao Ni

Xianmiao Ni received the BS degree in electronic science and technology from Harbin University of Science and Technology (HUST) in 2013. He is currently working toward the ME degree with BUPT, China. His research interests include energy-efficient resource management and energy harvesting in heterogeneous wireless networks.

E-mail: [email protected]