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Energy Efficiency Optimization for NOMA with SWIPT.pdf (444.69 kB)

Energy Efficiency Optimization for NOMA with SWIPT

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posted on 2019-04-04, 11:54 authored by J Tang, J Luo, M Liu, DKC So, E Alsusa, G Chen, KK Wong, J Chambers
IEEE The combination of simultaneous wireless information and power transfer (SWIPT) and non-orthogonal multiple access (NOMA) is a potential solution to improve spectral efficiency (SE) and energy efficiency (EE) of the upcoming fifth generation (5G) networks, especially in order to support the functionality of the Internet of things (IoT) and the massive machine-type communications (mMTC) scenarios. In this paper, we investigate joint power allocation and time switching (TS) control for EE optimization in a TS-based SWIPT NOMA system. Our aim is to optimize the EE of the system whilst satisfying the constraints on maximum transmit power budget, minimum data rate and minimum harvested energy per-terminal. The considered EE optimization problem is neither linear nor convex involving joint optimization of power allocation and time switching factors, and thus is extremely difficult to solve directly. In order to tackle this problem, we develop a dual-layer algorithm where Dinkelbach method is employed both in the inner-layer to optimize the power allocation and in the outer-layer to control the time switching assignment. Furthermore, a simplified but practical special case with equal time switching factors in all terminals is considered. Numerical results validate the theoretical findings and demonstrate that significant performance gain over orthogonal multiple access (OMA) scheme in terms of EE can be achieved by the proposed algorithms in a SWIPT-enabled NOMA system.

Funding

Engineering and Physical Sciences Research Council; National Natural Science Foundation of China

History

Citation

IEEE Journal on Selected Topics in Signal Processing, 2019, in press

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Engineering

Version

  • AM (Accepted Manuscript)

Published in

IEEE Journal on Selected Topics in Signal Processing

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

issn

1932-4553

eissn

1941-0484

Copyright date

2018

Available date

2019-04-04

Publisher version

https://ieeexplore.ieee.org/document/8636993/authors#authors

Language

en

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