Loh, Ser Lee and Keek, Joe Siang and Wong, Yan Chiew and Woo, Xiu Juan and Lee, Wei Wen (2021) Genetic Algorithms And Particle Swarm Optimization For Interference Minimization In Mobile Network Channel Assignment Problem. International Journal of Intelligent Engineering and Systems, 14 (4). pp. 276-288. ISSN 2185-310X
![[img]](http://eprints.utem.edu.my/style/images/fileicons/text.png) |
Text
INASS.PDF Download (644kB) |
Abstract
Interference minimization in cellular network has and will always be top priority, whether in current or future generation of cellular technology. Therefore, cellular channel assignment problem (CAP) requires continuous study and research. This paper presents the study and comparison of Genetic Algorithm (GA) and Particle Swam Optimization (PSO) for CAP in minimizing interference. GA with three variants in term of population selection – roulette wheel selection (RWS), tournament selection (TS) and stochastic universal sampling (SUS) were studied, and then compared with classic PSO. Two CAPs were derived and used to comprehensively evaluate the performances of the PSO and GAs. It was found that GA-TS is ~11% and ~7% faster than GA-RWS and GA-SUS, respectively. Although the difference is small, but it allowed GA-TS to run for few more iterations and eventually achieved better interference minimization. Moreover, it was also found that GA-SUS has less noise and produce a more consistent result. On the other hand, PSO is slower than GA-TS, but has higher potential to converge on smaller minimum value.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Channel Assignment Problem, Spectrum Sharing, Genetic Algorithm, Roulette Wheel Selection, Tournament Selection, Stochastic Universal Sampling, Particle Swarm Optimization. |
| Divisions: | Faculty of Electrical Engineering > Department of Mechatronics Engineering |
| Depositing User: | Norfaradilla Idayu Ab. Ghafar |
| Date Deposited: | 14 Mar 2022 10:46 |
| Last Modified: | 14 Mar 2022 10:46 |
| URI: | http://eprints.utem.edu.my/id/eprint/25667 |
| Statistic Details: | View Download Statistic |
Actions (login required)
 |
View Item |