5G 이동통신 셀 설계를 위한 타부 탐색과 유전 알고리즘의 성능
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 권오현 | - |
dc.contributor.author | 안흥섭 | - |
dc.contributor.author | 최승원 | - |
dc.date.accessioned | 2021-07-30T05:12:01Z | - |
dc.date.available | 2021-07-30T05:12:01Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2017-09 | - |
dc.identifier.issn | 1738-6667 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3489 | - |
dc.description.abstract | The fifth generation(5G) of wireless networks will connect not only smart phone but also unimaginable things. Therefore, 5G cellular network is facing the soaring traffic demand of numerous user devices. To solve this problem, a huge amount of 5G base stations will need to be installed. The base station positioning problem is an NP-hard problem that does not know how long it will take to solve the problem. Because, it can not find an answer other than to check the number of all cases. In this paper, to solve the NP hard problem, we compare the tabu search and the genetic algorithm using real maps for optimal cell planning. We also perform Monte Carlo simulations to study the performance of the Tabu search and Genetic algorithm for 5G cell planning. As a results, Tabu search required 2.95 times less computation time than Genetic algorithm and showed accuracy difference of 2dBm. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | (사)디지털산업정보학회 | - |
dc.title | 5G 이동통신 셀 설계를 위한 타부 탐색과 유전 알고리즘의 성능 | - |
dc.title.alternative | Performance comparison of Tabu search and genetic algorithm for cell planning of5G cellular network | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 최승원 | - |
dc.identifier.doi | 10.17662/ksdim.2017.13.3.065 | - |
dc.identifier.bibliographicCitation | (사)디지털산업정보학회 논문지, v.13, no.3, pp.65 - 73 | - |
dc.relation.isPartOf | (사)디지털산업정보학회 논문지 | - |
dc.citation.title | (사)디지털산업정보학회 논문지 | - |
dc.citation.volume | 13 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 65 | - |
dc.citation.endPage | 73 | - |
dc.type.rims | ART | - |
dc.identifier.kciid | ART002268990 | - |
dc.description.journalClass | 2 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | kci | - |
dc.description.journalRegisteredClass | other | - |
dc.subject.keywordAuthor | 5G | - |
dc.subject.keywordAuthor | Cell Planning | - |
dc.subject.keywordAuthor | Meta-heuristic | - |
dc.subject.keywordAuthor | Tabu Serach | - |
dc.subject.keywordAuthor | Genetic Algorithm | - |
dc.identifier.url | http://koreascience.or.kr/article/JAKO201730475988639.page | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.