Journal of Korea Society of Digital Industry and Information Management (디지털산업정보학회논문지)

Korea Society of Digital Industry and Information Management (디지털산업정보학회)
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Performance comparison of Tabu search and genetic algorithm for cell planning of 5G cellular network

5G 이동통신 셀 설계를 위한 타부 탐색과 유전 알고리즘의 성능

  • 권오현 (한양대학교 전자컴퓨터통신공학과) ;
  • 안흥섭 (한양대학교 전자컴퓨터통신공학과) ;
  • 최승원 (한양대학교 전자컴퓨터통신공학과)
  • Received : 2017.08.22
  • Accepted : 2017.09.14
  • Published : 2017.09.30
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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.

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