Performance evaluation of multi-user detection in Cdma using micro-genetic algorithm
Two main problem of multi-user communication system are the Multiple Access Interference (MAI) and the near-far effects. While near-far effect problem can be approach by applying power control, the MAI problem requires individual receiver to identify desired signal from interferences thus making mul...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2005
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/37308/1/01635519.pdf http://irep.iium.edu.my/37308/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1635519&tag=1 |
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| Summary: | Two main problem of multi-user communication system are the Multiple Access Interference (MAI) and the near-far effects. While near-far effect problem can be approach by applying power control, the MAI problem requires individual receiver to identify desired signal from interferences thus making multi-user detector a popular area of research. Genetic Algorithms (GA) is a search and optimizes technique that works by estimating multiple solutions in order to come with the best estimated solution. GA works iteratively over a population of solution using crossover and mutation to simulate potential solution. In this paper we examine the performance of a micro-Genetic Algorithm-based multi-user detector. Our simulation shows that μGA achieves a performance close to optimal detector. |
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