MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks
The modernization of smart devices has emerged in exponential growth in data traffic for a high-capacity wireless network. 5G networks must be capable of handling the excessive stress associated with resource allocation methods for its successful deployment. We also need to take care of the problem...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2017/4353612 |
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| _version_ | 1832564230095634432 |
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| author | Ruchi Sachan Zahid Muhammad Jaehoon (Paul) Jeong Chang Wook Ahn Hee Yong Youn |
| author_facet | Ruchi Sachan Zahid Muhammad Jaehoon (Paul) Jeong Chang Wook Ahn Hee Yong Youn |
| author_sort | Ruchi Sachan |
| collection | DOAJ |
| description | The modernization of smart devices has emerged in exponential growth in data traffic for a high-capacity wireless network. 5G networks must be capable of handling the excessive stress associated with resource allocation methods for its successful deployment. We also need to take care of the problem of causing energy consumption during the dense deployment process. The dense deployment results in severe power consumption because of fulfilling the demands of the increasing traffic load accommodated by base stations. This paper proposes an improved Artificial Bee Colony (ABC) algorithm which uses the set of variables such as the transmission power and location of each base station (BS) to improve the accuracy of localization of a user equipment (UE) for the efficient energy consumption at BSes. To estimate the optimal configuration of BSes and reduce the power requirement of connected UEs, we enhanced the ABC algorithm, which is named a Modified ABC (MABC) algorithm, and compared it with the latest work on Real-Coded Genetic Algorithm (RCGA) and Differential Evolution (DE) algorithm. The proposed algorithm not only determines the optimal coverage of underutilized BSes but also optimizes the power utilization considering the green networks. The performance comparisons of the modified algorithms were conducted to show that the proposed approach has better effectiveness than the legacy algorithms, ABC, RCGA, and DE. |
| format | Article |
| id | doaj-art-f0b56df56db243208db0831402aadc2f |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-f0b56df56db243208db0831402aadc2f2025-02-03T01:11:37ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2017-01-01201710.1155/2017/43536124353612MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G NetworksRuchi Sachan0Zahid Muhammad1Jaehoon (Paul) Jeong2Chang Wook Ahn3Hee Yong Youn4Department of Computer Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of KoreaDepartment of Computer Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of KoreaDepartment of Interaction Science, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of KoreaSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-ro, Buk-gu, Gwangju 61005, Republic of KoreaDepartment of Computer Engineering, Sungkyunkwan University, Suwon, Republic of KoreaThe modernization of smart devices has emerged in exponential growth in data traffic for a high-capacity wireless network. 5G networks must be capable of handling the excessive stress associated with resource allocation methods for its successful deployment. We also need to take care of the problem of causing energy consumption during the dense deployment process. The dense deployment results in severe power consumption because of fulfilling the demands of the increasing traffic load accommodated by base stations. This paper proposes an improved Artificial Bee Colony (ABC) algorithm which uses the set of variables such as the transmission power and location of each base station (BS) to improve the accuracy of localization of a user equipment (UE) for the efficient energy consumption at BSes. To estimate the optimal configuration of BSes and reduce the power requirement of connected UEs, we enhanced the ABC algorithm, which is named a Modified ABC (MABC) algorithm, and compared it with the latest work on Real-Coded Genetic Algorithm (RCGA) and Differential Evolution (DE) algorithm. The proposed algorithm not only determines the optimal coverage of underutilized BSes but also optimizes the power utilization considering the green networks. The performance comparisons of the modified algorithms were conducted to show that the proposed approach has better effectiveness than the legacy algorithms, ABC, RCGA, and DE.http://dx.doi.org/10.1155/2017/4353612 |
| spellingShingle | Ruchi Sachan Zahid Muhammad Jaehoon (Paul) Jeong Chang Wook Ahn Hee Yong Youn MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks Discrete Dynamics in Nature and Society |
| title | MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks |
| title_full | MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks |
| title_fullStr | MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks |
| title_full_unstemmed | MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks |
| title_short | MABC: Power-Based Location Planning with a Modified ABC Algorithm for 5G Networks |
| title_sort | mabc power based location planning with a modified abc algorithm for 5g networks |
| url | http://dx.doi.org/10.1155/2017/4353612 |
| work_keys_str_mv | AT ruchisachan mabcpowerbasedlocationplanningwithamodifiedabcalgorithmfor5gnetworks AT zahidmuhammad mabcpowerbasedlocationplanningwithamodifiedabcalgorithmfor5gnetworks AT jaehoonpauljeong mabcpowerbasedlocationplanningwithamodifiedabcalgorithmfor5gnetworks AT changwookahn mabcpowerbasedlocationplanningwithamodifiedabcalgorithmfor5gnetworks AT heeyongyoun mabcpowerbasedlocationplanningwithamodifiedabcalgorithmfor5gnetworks |