Research Article
Energy Efficient Clustering and Beamforming for Cooperative Multicell Networks
@INPROCEEDINGS{10.1007/978-3-319-47509-7_3, author={Yawen Chen and Xiangming Wen and Zhaoming Lu and Hua Shao and Jingyu Lu and WenPeng Jing}, title={Energy Efficient Clustering and Beamforming for Cooperative Multicell Networks}, proceedings={Game Theory for Networks. 6th International Conference, GameNets 2016, Kelowna, BC, Canada, May 11-12, 2016, Revised Selected Papers}, proceedings_a={GAMENETS}, year={2017}, month={1}, keywords={Cooperative transmission Energy efficiency Beamforming Clustering Coalition formation game}, doi={10.1007/978-3-319-47509-7_3} }- Yawen Chen
Xiangming Wen
Zhaoming Lu
Hua Shao
Jingyu Lu
WenPeng Jing
Year: 2017
Energy Efficient Clustering and Beamforming for Cooperative Multicell Networks
GAMENETS
Springer
DOI: 10.1007/978-3-319-47509-7_3
Abstract
Network densification is the most important way to improve the network capacity and hence is widely adopted to handle the ever-increasing mobile traffic demand. However, network densification will make the inter-cell interference severe and also significantly increase the energy budget. Multicell cooperative transmission is an efficient way to mitigate the inter-cell interference and plays an important role in energy efficiency optimization. This paper investigates the energy efficient multicell cooperation strategy for dense wireless networks. Joint cluster forming and beamforming are considered to optimize the energy efficiency (evaluated by bits/Hz/J). The optimization problem is then decoupled into two subproblems, i.e., energy efficient beamforming problem and energy efficient cluster forming problem. The fractional programming and Lagrangian duality theory are used to obtain the optimal beamformer. Coalition formation game theory is exploited to solve the cluster forming problem. The proposed energy efficient clustering and beamforming strategy can provide flexible network service according to spatially uneven traffic and greatly improve the network energy efficiency.