An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network
Abstract Recently, the 5G as the next‐generation network is a popular research and discussed widely. The architecture of 5G is a heterogeneous network, and it can support more networked types, like the ultra‐dense network, traditional cellular network, and Machine to Machine communication. Although...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-07-01
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| Series: | IET Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cmu2.12263 |
| _version_ | 1811183646391926784 |
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| author | Shih‐Yun Huang Hsin‐Hung Cho Yao‐Chung Chang Jie‐Yu Yuan Han‐Chieh Chao |
| author_facet | Shih‐Yun Huang Hsin‐Hung Cho Yao‐Chung Chang Jie‐Yu Yuan Han‐Chieh Chao |
| author_sort | Shih‐Yun Huang |
| collection | DOAJ |
| description | Abstract Recently, the 5G as the next‐generation network is a popular research and discussed widely. The architecture of 5G is a heterogeneous network, and it can support more networked types, like the ultra‐dense network, traditional cellular network, and Machine to Machine communication. Although the high frequency and larger bandwidth have been using in 5G, resource allocation is still a critical issue that needs to be discussed and solved. Consider the spectrum resource is limited, but almost all users hope that equipment can get a better quality of services. Therefore, how to manage the spectrum resource and allocation is a big problem. Consider the fast‐growing devices and traffic in the future; hence, task scheduling for UEs to reduce energy consumption will be focused on. To solve resource allocation and minimise energy consumption, the Markov decision chain is proposed to be used to predict the channel state. The modified particle swarm optimization (MPSO) is also used in this paper to find the best task scheduling. The simulation will be used to verify the performance of the mechanism that is used and compare it with PSO and first‐in‐first‐service (FIFS). The result shows the method used can be scheduled for the task efficiently. |
| first_indexed | 2024-04-11T09:50:24Z |
| format | Article |
| id | doaj.art-1186b9de4ba24da48c9c17ce0a1548eb |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-04-11T09:50:24Z |
| publishDate | 2022-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-1186b9de4ba24da48c9c17ce0a1548eb2022-12-22T04:30:50ZengWileyIET Communications1751-86281751-86362022-07-0116111268127810.1049/cmu2.12263An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile networkShih‐Yun Huang0Hsin‐Hung Cho1Yao‐Chung Chang2Jie‐Yu Yuan3Han‐Chieh Chao4Department of Electrical Engineering National Dong Hwa University Hualien TaiwanDepartment of Computer Science and Information Engineering National Ilan University I‐Lan TaiwanDepartment of Computer Science and Information Engineering National Taitung University Taitung TaiwanDepartment of Electrical Engineering National Dong Hwa University Hualien TaiwanDepartment of Electrical Engineering National Dong Hwa University Hualien TaiwanAbstract Recently, the 5G as the next‐generation network is a popular research and discussed widely. The architecture of 5G is a heterogeneous network, and it can support more networked types, like the ultra‐dense network, traditional cellular network, and Machine to Machine communication. Although the high frequency and larger bandwidth have been using in 5G, resource allocation is still a critical issue that needs to be discussed and solved. Consider the spectrum resource is limited, but almost all users hope that equipment can get a better quality of services. Therefore, how to manage the spectrum resource and allocation is a big problem. Consider the fast‐growing devices and traffic in the future; hence, task scheduling for UEs to reduce energy consumption will be focused on. To solve resource allocation and minimise energy consumption, the Markov decision chain is proposed to be used to predict the channel state. The modified particle swarm optimization (MPSO) is also used in this paper to find the best task scheduling. The simulation will be used to verify the performance of the mechanism that is used and compare it with PSO and first‐in‐first‐service (FIFS). The result shows the method used can be scheduled for the task efficiently.https://doi.org/10.1049/cmu2.12263Optimisation techniquesMobile radio systemsOptimisation techniques |
| spellingShingle | Shih‐Yun Huang Hsin‐Hung Cho Yao‐Chung Chang Jie‐Yu Yuan Han‐Chieh Chao An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network IET Communications Optimisation techniques Mobile radio systems Optimisation techniques |
| title | An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network |
| title_full | An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network |
| title_fullStr | An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network |
| title_full_unstemmed | An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network |
| title_short | An efficient spectrum scheduling mechanism using Markov decision chain for 5G mobile network |
| title_sort | efficient spectrum scheduling mechanism using markov decision chain for 5g mobile network |
| topic | Optimisation techniques Mobile radio systems Optimisation techniques |
| url | https://doi.org/10.1049/cmu2.12263 |
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