Energy-limited ant colony optimization with cooperative transmission

Hamzah, Mohd Hazmi; Ghani, Hadhrami bin Ab

doi:10.1109/i4ct.2014.6914167

Cited by 3 publications

(4 citation statements)

References 19 publications

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“…Ants exchange information with others during their search expeditions using informal contact, such as "stigmergy" [18], and do so by producing traces of pheromones for other ants to detect food sources [19,20]. ACO has been proposed to be integrated in various generations of cellular network technologies [21][22][23]. As the ACO scheme is also compliant with 5G, the purpose of this paper is to further extend and incorporate this 5G solution with a greater number of NOMA antennas and users.…”

Section: Ant-colony Optimization Modelmentioning

confidence: 99%

Ant-Colony Based User Grouping Modelling for Fast Cellular Networks

Alhanik

Hamzah

Ghani

et al. 2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

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The need for efficient allocation of radio bandwidth to the users in the current and future cellular networks is high. As more users are requesting for the network connections, the radio bandwidth must be fairly and efficiently allocated. The non-orthogonal multiple access (NOMA), which has been introduced for 5G networks, is useful to allow bandwidth sharing among the users, rendering a more efficient allocation and utilization of the bandwidth. However, the computational load required to determine and select the users for each of the radio resources tends to increase as the total number of users rises. Therefore, user grouping that requires lower computational complexity such as the heuristic methods are useful to address this problem. An ant-colony optimization has been applied in this paper to perform user grouping in 5G NOMA. The mean throughput and mean square error have been measured when testing the proposed scheme. The result shows that the proposed scheme produces satisfactory throughput results, close to that of the theoretical upper limit. The mean square error is also close to the lower limit and better than the existing scheme.

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Section: Ant-colony Optimization Modelmentioning

confidence: 99%

Ant-Colony Based User Grouping Modelling for Fast Cellular Networks

Alhanik

Hamzah

Ghani

et al. 2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

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“…Several methods are proposed for the formation of user pairs such as round robin [28]. As these approaches tend to require significantly higher computational loads when the number of users increases, new computationally lower schemes have been proposed in literature to determine the user pairs such as the heuristic models which are inspired by artificial intelligence approaches [29][30][31][32][33][34] which include drosophila optimization algorithm [35], particle swarm optimization algorithm [36][37][38], firefly optimization algorithm [39], dolphin echolocation algorithm [40], genetic algorithm [20,41] and ant-colony optimization algorithm [19,42]. These models have the ability to solve problems in varying fields such as, but not limited to, transportation, signal processing, image processing and biomedical engineering.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Firefly optimization and particle swarm optimization require a smaller number of parameters but so far implemented with a small number of users per sub channel. The practical solution provided by ACO [19,42,51] method for NOMA is useful as the number of mobile users using the cellular network services keeps increasing in this age. It is a method worth to be implemented and further developed and presented in the research and academic community.…”

Section: Future Workmentioning

confidence: 99%

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

Liyn

Ghani²,

Roslim³

et al. 2020

TELKOMNIKA

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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.

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“…Fourier Transform is first introduced by Jean Baptiste Joseph Fourier [1] to solve the computational complexity in wide varities of fields including earth and science, chemistry, communications, and signal processing [2][3][4][5]. In signal processing, Fourier Transform [6][7][8][9][10][11] has long been established as an instrumental tool applied in electrical signal spectrum and filter analysis, sampling and series, antenna, television image convolution as well as radio broadcasting [1]. Being the limiting case of Fourier Series for non-periodic signals, FT is used to convert signal to frequency domain as the frequency domain has many superlative benefits especially for analytical purposes rather than in the classical time domain.…”

Section: Introductionmentioning

confidence: 99%

A review on sparse fast fourier transform applications in image processing

Ghani

Malek

Azmi

et al. 2020

IJECE

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Fast Fourier Transform has long been established as an essential tool in signal processing. To address the computational issues while helping the analysis work for multi-dimensional signals in image processing, sparse Fast Fourier Transform model is reviewed here when applied in different applications such as lithography optimization, cancer detection, evolutionary arts and wasterwater treatment. As the demand for higher dimensional signals in various applications especially multimedia appplications, the need for sparse Fast Fourier Transform grows higher.

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Energy-limited ant colony optimization with cooperative transmission

Cited by 3 publications

References 19 publications

Ant-Colony Based User Grouping Modelling for Fast Cellular Networks

Ant-Colony Based User Grouping Modelling for Fast Cellular Networks

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

A review on sparse fast fourier transform applications in image processing

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