@article{2a398a925fc24d4c9dfaad935ff14e26,
title = "Energy Efficient Resource Management in SWIPT Enabled Heterogeneous Networks with NOMA",
abstract = "Non-orthogonal multiple access (NOMA) in heterogeneous network (HetNet) is a very promising scheme to meet the exponential growth of mobile data expected in the coming years. However, since wireless networks are becoming denser, the energy consumption of such networks is increasingly severe. Therefore, it is necessary to design novel energy efficiency (EE) maximization technologies under the constraint of limited energy supply. This paper investigates the resource optimization problem of NOMA heterogeneous small cell networks with simultaneous wireless information and power transfer (SWIPT). By decoupling subchannel allocation and power control, a low-complexity subchannel matching algorithm is designed. Furthermore, to maximize the energy efficiency, a power optimization algorithm is proposed using Langrangian duality. Aiming at the power allocation problem, the original non-convex and non-linear energy efficiency optimization problem is transformed into a more tractable one. Simulation results demonstrate the effectiveness and convergence of the proposed optimization scheme in terms of system energy efficiency.",
keywords = "Energy efficiency, HetNets, NOMA, energy harvesting, resource allocation",
author = "Haijun Zhang and Mengting Feng and Keping Long and Karagiannidis, {George K.} and Leung, {Victor C.M.} and Poor, {H. Vincent}",
note = "Funding Information: Manuscript received May 8, 2019; revised August 31, 2019; accepted October 10, 2019. Date of publication November 5, 2019; date of current version February 11, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61822104 and Grant 61771044, in part by the Beijing Natural Science Foundation under Grant L172025 and Grant L172049, in part by the 111 Project under Grant B170003, in part by the Fundamental Research Funds for the Central Universities under Grant FRF-TP-19-002C1, and in part by the U.S. National Science Foundation under Grant CCF-0939370. This article was presented in part at the IEEE Global Communications Conference (Globecom 2018), Abu Dhabi, UAE, 2018. The associate editor coordinating the review of this article and approving it for publication was P. Salvo Rossi. (Corresponding authors: Haijun Zhang; Keping Long.) H. Zhang, M. Feng, and K. Long are with the Institute of Artificial Intelligence, the Beijing Advanced Innovation Center for Materials Genome Engineering, Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing, Beijing 100083, China (e-mail: haijunzhang@ieee.org; g20178656@xs.ustb.edu.cn; longkeping@ustb.edu.cn). Publisher Copyright: {\textcopyright} 2002-2012 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = feb,
doi = "10.1109/TWC.2019.2948874",
language = "English (US)",
volume = "19",
pages = "835--845",
journal = "IEEE Transactions on Wireless Communications",
issn = "1536-1276",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",
}