Journal of electromagnetic engineering and science

The Korean Institute of Electromagnetic Engineering and Science (한국전자파학회)
권호 표지

Improvement of Minimum MSE Performance in LMS-type Adaptive Equalizers Combined with Genetic Algorithm

  • Kim, Nam-Yong (Dept. of Information ＆ Communication Eng., SamCheok National University)
  • Published : 2004.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper the Individual tap - Least Mean Square(IT-LMS) algorithm is applied to the adaptive multipath channel equalization using hybrid-type Genetic Algorithm(GA) for achieving lower minimum Mean Squared Error(MSE). Owing to the global search performance of GA, LMS-type equalizers combined with it have shown preferable performance in both global and local search but those still have unsatisfying minimum MSE performance. In order to lower the minimum MSE we investigated excess MSE of IT-LMS algorithm and applied it to the hybrid GA equalizer. The high convergence rate and lower minimum MSE of the proposed system give us reason to expect that it will perform well in practical multi-path channel equalization systems.

Keywords

References

  1. Proceedings of the 1998 Second International Conference of Knowledge-Based Intelligent Electronic Systems v.3 A Hybrid GA/SA Approach to Blind Deconvolution Yeb-Wei Chen;Tatsuro Enokura;Zensho Nakao
  2. Proc. Int. Joint Conf. Artificial Intelligence Training Feedforward Neural Networks Using Genetic Algorithms D.J.Montana;L.Davis
  3. Proc. IEEE Int. Conf. on ASSP Recursive Adaptive Filter Design using an A daptive Genetic Algorithm D.M.Etter;M.J.Hicks;K.H.Cho
  4. IEEE Trans. on Signal Processing v.46 no.5 Maximum Likelihood Joint Channel and Data Estimation Using Genetic Algorithms S.Chen;Y.Wu https://doi.org/10.1109/78.668813
  5. Proceedings of the ICSPAT v.1 GA-LMS Algorithm for Adaptive System Identification Sung-Hwan Han;Hyeon-Ho Kim;Young-Ki Han;Seo-Yong Park
  6. The Journal of The Korean Institute of Communication Sciences v.17 no.3 Analysis of the excess MSE of the Individual Tap LMS(IT-LMS) equalizer Nam-Yong Kim;Young Jo Lee;Chang Eon Kang
  7. Proceedings of the 1997 IEEE International Intermag '97 Magnetics Conference A Theoretical Analysis of the Non-Uniform Mutation Operator for the Modified Genetic Algorithm A.Neubauer
  8. Proceedings of the 23rd International Conference on Industrial Electronics, Control, and Instrumentation v.4 Genetic Algorithms for Control and Signal Processing K.F.Man;K.S.Tang
  9. Genetic Algorithms + Data Strucpture's Evolution Program(3nd Ed.) Z.Michalewicz
  10. IEEE Signal Processing Magazine Genetic Algorithms and their applications K.S.Tang;K.F.Man;S.Kwong;Q.He
  11. IEEE Trans. on Signal Processing v.42 Nonlinear Parameter Estimation via the Genetic Algorithm L.Yao;W.A.Sethares https://doi.org/10.1109/78.285655
  12. IEE Proc. v.128 Adaptive mean-square-error transversal equalizer M.J.Hawksford;N.Razaee
  13. Digital Communications J.G.Proakis
  14. Adaptive Signal Processing B.Widrow
  15. IEEE International Symposium on Intelligent Signal Processing and Communication Systems Adaptive Equalizers using GA and LMS type Algorithms Nam-Yong Kim;Hyung-Gi Gyun