Ant-colony and nature-inspired heuristic models for NOMA systems: a review

Citation

Liyn, Law Poh and Ab. Ghani, Hadhrami and Roslim, Farah Najwa and Amir Hamzah, Nur Asyiqin and Abdulghani Mohammed, Saeed Mohammed and Abdul Aziz, Nor Hidayati and Abd. Aziz, Azlan and Tan, Kim Geok and Azizan, Azizul (2020) Ant-colony and nature-inspired heuristic models for NOMA systems: a review. TELKOMNIKA, 18 (4). p. 1754. ISSN 1693-6930

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Abstract

The increasing computational complexity in scheduling the large number of users for non-orthogonal multiple access (NOMA) system and future cellular networks lead to the need for scheduling models with relatively lower computational complexity such as heuristic models. The main objective of this paper is to conduct a concise study on ant-colony optimization (ACO) methods and potential nature-inspired heuristic models for NOMA implementation in future high-speed networks. The issues, challenges and future work of ACO and other related heuristic models in NOMA are concisely reviewed. The throughput result of the proposed ACO method is observed to be close to the maximum theoretical value and stands 44% higher than that of the existing method. This result demonstrates the effectiveness of ACO implementation for NOMA user scheduling and grouping

Item Type: Article
Uncontrolled Keywords: Heuristic algorithms, Ant-colony, Heuristic, Orthogonal
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 21 Dec 2020 05:53
Last Modified: 21 Dec 2020 07:08
URII: http://shdl.mmu.edu.my/id/eprint/7881

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