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DOI: 10.14569/IJACSA.2021.0120240
PDF

Optimal Power Allocation in Downlink Non-Orthogonal Multiple Access (NOMA)

Author 1: Wajd Fahad Alghasmari
Author 2: Laila Nassef

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 2, 2021.

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Abstract: Fifth generation of wireless cellular networks promise to enable better services anytime and anywhere. Non-orthogonal multiple access (NOMA) stands as a suitable multiple accessing scheme due to the ability to allow multiple users to share the same radio resource simultaneously via different domains (power, code, etc.). Through the introduced power domain, users multiplexed at the radio resource within different power levels. This paper studies power allocation in downlink NOMA, an optimization problem formulated that aims to maximize the system's sum rate. To solve the problem, a genetic algorithm based power allocation (GAPA) was proposed that uses genetic algorithm (GA) that employs heuristics to search for suitable solutions. The performance of the proposed power allocation algorithm compared with full search power allocation (FSPA) that gives an optimal performance. Results show that GAPA reaches a performance near to FSPA with lower complexity. In addition, GAPA simulated with various user paring algorithms. Channel state sorting based user pairing with GAPA achieves the best performance comparing to random user pairing algorithm and exhaustive user pairing.

Keywords: Non-orthogonal multiple access; power allocation; genetic algorithm; user pairing

Wajd Fahad Alghasmari and Laila Nassef, “Optimal Power Allocation in Downlink Non-Orthogonal Multiple Access (NOMA)” International Journal of Advanced Computer Science and Applications(IJACSA), 12(2), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120240

@article{Alghasmari2021,
title = {Optimal Power Allocation in Downlink Non-Orthogonal Multiple Access (NOMA)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120240},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120240},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {2},
author = {Wajd Fahad Alghasmari and Laila Nassef}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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