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Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks

Jianzhong Li1, DexiangMei1, Dong Deng1, Imran Khan2, Peerapong Uthansakul3, *
1 School of Finance, Chongqing Technology and Business University, Chongqing, China.
2 Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan.
3 School of Telecommunication Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand.
* Corresponding Author: Peerapong Uthansakul. Email: .

Computers, Materials & Continua 2020, 65(2), 1571-1590. https://doi.org/10.32604/cmc.2020.011822

Received 30 May 2020; Accepted 19 June 2020; Issue published 20 August 2020

Abstract

Non-orthogonal multiple access (NOMA) is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. NOMA allows multiple terminals to share the same resource unit at the same time. The receiver usually needs to configure successive interference cancellation (SIC). The receiver eliminates co-channel interference (CCI) between users and it can significantly improve the system throughput. In order to meet the demands of users and improve fairness among them, this paper proposes a new power allocation scheme. The objective is to maximize user fairness by deploying the least fairness in multiplexed users. However, the objective function obtained is non-convex which is converted into convex form by utilizing the optimal Karush-Kuhn-Tucker (KKT) constraints. Simulation results show that the proposed power allocation scheme gives better performance than the existing schemes which indicates the effectiveness of the proposed scheme.

Keywords

5G, NOMA, user fairness, resource optimization, multiple access scheme.

Cite This Article

J. Li, D. , D. Deng, I. Khan and P. Uthansakul, "Proportional fairness-based power allocation algorithm for downlink noma 5g wireless networks," Computers, Materials & Continua, vol. 65, no.2, pp. 1571–1590, 2020.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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