Genetic Algorithms And Particle Swarm Optimization For Interference Minimization In Mobile Network Channel Assignment Problem
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 Algo...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Intelligent Network and Systems Society
2021
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| Online Access: | http://eprints.utem.edu.my/id/eprint/25667/2/INASS.PDF http://eprints.utem.edu.my/id/eprint/25667/ https://oaji.net/articles/2021/3603-1624926784.pdf |
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| Summary: | 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. |
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