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  • 标题:Geneti Algorithm Optimization Tool for Channel Estimation and Symbol Detection in Mimo-OFDM Systems
  • 本地全文:下载
  • 作者:Apoorva S. Agrawal
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:11
  • 页码:45-54
  • DOI:10.14257/ijsip.2015.8.11.05
  • 出版社:SERSC
  • 摘要:The quality of wireless media is described by three parameters. These parameters are its transmission range, transmission rate and reliability. In the conventional OFDM systems one parameter can be increased on the cost of decreasing other two parameters. However by combining MIMO with OFDM systems, all the three parameters can be improved simultaneously. Symbol detection and channel estimation are the two essential tasks of MIMO-OFDM system. These tasks can be excellently achieved by various other recently developed algorithms such as maximum likelihood (ML) detector, LMS, RLS etc. All these algorithms face a common problem of robustness. Also the complexity of these algorithms is very high in the system with large number of transmitters and receivers and having large constellation size. Therefore, we are using the NLMS estimator. But it doesn't provide the optimal solution. Genetic algorithm has the advantages of significantly less computational complexity, greater robustness and is closer to the optimal solution. Hence in this paper we are using Genetic algorithm based NLMS estimator to accomplish these tasks and to achieve results near to optimal solution. Comparisons between the results obtain from GA optimized NLMS estimator and plane NLMS estimator has been shown for better understanding
  • 关键词:Genetic algorithm (GA); MIMO-OFDM systems; symbol detection; channel ; estimation
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