Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods
Abstract In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wir...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2020-09-01
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| Series: | EURASIP Journal on Wireless Communications and Networking |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13638-020-01798-y |
| _version_ | 1818492026054770688 |
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| author | Hafiz Munsub Ali Jiangchuan Liu Waleed Ejaz |
| author_facet | Hafiz Munsub Ali Jiangchuan Liu Waleed Ejaz |
| author_sort | Hafiz Munsub Ali |
| collection | DOAJ |
| description | Abstract In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources. |
| first_indexed | 2024-12-10T17:38:12Z |
| format | Article |
| id | doaj.art-29450f2e446f4d4b95c0aacbda8cbe7e |
| institution | Directory Open Access Journal |
| issn | 1687-1499 |
| language | English |
| last_indexed | 2024-12-10T17:38:12Z |
| publishDate | 2020-09-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Wireless Communications and Networking |
| spelling | doaj.art-29450f2e446f4d4b95c0aacbda8cbe7e2022-12-22T01:39:27ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992020-09-012020112410.1186/s13638-020-01798-yPlanning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methodsHafiz Munsub Ali0Jiangchuan Liu1Waleed Ejaz2School of Engineering Science, Simon Fraser UniversitySchool of Computing Science, Simon Fraser UniversityDepartment of Electrical Engineering, Lakehead University-Barrie CampusAbstract In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources.http://link.springer.com/article/10.1186/s13638-020-01798-yFifth generation and beyond wireless networksSwarm intelligenceFireworks algorithmEnsemble of local search methods |
| spellingShingle | Hafiz Munsub Ali Jiangchuan Liu Waleed Ejaz Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods EURASIP Journal on Wireless Communications and Networking Fifth generation and beyond wireless networks Swarm intelligence Fireworks algorithm Ensemble of local search methods |
| title | Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods |
| title_full | Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods |
| title_fullStr | Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods |
| title_full_unstemmed | Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods |
| title_short | Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods |
| title_sort | planning capacity for 5g and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods |
| topic | Fifth generation and beyond wireless networks Swarm intelligence Fireworks algorithm Ensemble of local search methods |
| url | http://link.springer.com/article/10.1186/s13638-020-01798-y |
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