Research Article
Green Resource Allocation in Intelligent Software Defined NOMA Networks
@INPROCEEDINGS{10.1007/978-3-319-73447-7_46, author={Baobao Wang and Haijun Zhang and Keping Long and Gongliang Liu and Xuebin Li}, title={Green Resource Allocation in Intelligent Software Defined NOMA Networks}, proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II}, proceedings_a={MLICOM}, year={2018}, month={2}, keywords={Energy efficient NOMA SDN Resource allocation}, doi={10.1007/978-3-319-73447-7_46} }- Baobao Wang
Haijun Zhang
Keping Long
Gongliang Liu
Xuebin Li
Year: 2018
Green Resource Allocation in Intelligent Software Defined NOMA Networks
MLICOM
Springer
DOI: 10.1007/978-3-319-73447-7_46
Abstract
Non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) is a promising technique for fifth generation wireless communications. In NOMA, multiple users can access the same frequency-time resource simultaneously and multi-user signals can be separated successfully with SIC. In this paper, with recent advances in software-defined networking (SDN), an architecture of SDN-NOMA network was proposed and the SDN controller has a global view of the network. We aim to investigate the resource allocation algorithms for the virtual resource blocks (VRB) assignment and power allocation for the downlink SDN-NOMA network. Different from the existing works, here, energy efficient dynamic power allocation in SDN-NOMA networks is investigated with the constraints of QoS requirement and power consumption. The simulation results confirm that the proposed scheme of SDN-NOMA system yields much better sum rate and energy efficiency performance than the conventional orthogonal frequency division multiple access scheme.