Abstract
Because of the fact that mobile communication channel changes by time, it is necessary to employ adaptive channel equalizers in order to combat the distorting effects of the channel. Least Mean Squares (LMS) algorithm is one of the most popular channel equalization algorithms and is preferred over other algorithms such as the Recursive Least Squares (RLS) and Maximum Likelihood Sequence Estimation (MLSE) when simplicity is a dominant decision factor. However, LMS algorithm suffers from poor performance and convergence speed within the training period specified by most of the standards. The aim of this study is to improve the convergence speed and performance of the LMS algorithm by adjusting the step size using fuzzy logic. The proposed method is compared with the Channel Matched Filter-Decision Feedback Equalizer (CMF-DFE) [1] which provides multi path propagation diversity by collecting the energy in the channel, Minimum Mean Square Error-Decision Feedback Equalizer (MMSE-DFE) [2] which is one of the most successful equalizers for the data packet transmission, normalized LMS-DFE (N-LMS-DFE) [3], variable step size (VSS) LMS-DFE [4], fuzzy LMS-DFE [5,6] and RLS-DFE [7]. The obtained simulation results using HIPERLAN/1 standards have demonstrated that the proposed LMS-DFE algorithm based on fuzzy logic has considerably better performance than others.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baltac1, Y., Kaya, I., Nix, A.R.: Implementation of a HIPERLAN/1 Compatible CMF-DFE Equalizer. VTC 2000. In: IEEE 51st Vehicular Technology Conference Proceedings, Tokyo, pp. 1884–1888 (2000)
Klein, A.: Zero Forcing and Minimum Mean-Square-Error Equalization for Multi-user Detection in Code Division Multiple-Access Channels. IEEE Transactions on Vehicular Technology 45, 276–286 (1997)
Hayes, M.H.: Statistical Digital Signal Processing and Modeling. John Wiley & Sons, Chichester (1996)
Kwong, R.H., Johnston, E.W.: A Variable Step Size LMS Algorithm. IEEE Transactions on Signal Processing 40, 1633–1642 (1992)
Ryu, G.T., Kim, D.W., Choe, J.G., Kim, D.S, Bae, H.D.: Adaptive System Identification Using Fuzzy Inference Based LMS Algorithm. In: IEEE 3rd International Conference on Signal Processing, vol. 1, pp. 587–590 (1996)
Gan, W.S.: Designing a Fuzzy Step Size LMS Algorithm. IEE Proceedings Visual Image Signal Processing 144, 261–266 (1997)
Proakis, J.G.: Digital Communications. McGraw-Hill Co., Singapore( (2001)
Sklar, B.: Rayleigh Fading Channels in Mobile Digital Communication Systems, pp. 90–100. IEEE Computer Society Press, Los Alamitos (1997)
Haddad, M.I., Khasawneh, M.A.: A Modified Variable Degree Variable Step Size LMS Algorithm. In: Proceedings of IEEE Midwest Symposium on Circuit and Systems, pp. 506–509. IEEE Computer Society Press, Los Alamitos (1998)
Park, D.J.: New Performance Function and Variable Step Size LMS Algorithm Derived by Karni and Zeng. IEE Electronics Letters 27, 2182–2183 (1991)
Haris, R.W., Chabries, D.M., Bishop, F.A.: A Variable Step (VS) Adaptive Filter Algorithm. IEEE Transactions on Acoustics, Speech and Signal Processing 34, 309–316 (1986)
Özen A.: A Fuzzy Based Outer Loop Controller Design Improving the Performance and Convergence Speed in High Data Rate Digital Communication Receivers. Ph.D. Thesis, Graduate School of Natural and Applied Science, KTU, Trabzon (2005)
Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)
Mamdani, E.H.: Application of Fuzzy Algorithms for Control of Simple Dynamic Plant. Proc. IEE 12, 1585–1588 (1974)
Su, P.V., Tuan, L.M., Kim, J., Yoon, G.: A New Fuzzy Logic Application to Variable Step Size LMS Algorithm for Adaptive Antennas in CDMA Systems. In: IEEE 3rd International Conference on Microwave and Millimeter Wave Technology Proceedings, pp. 685–688 (2002)
Eminoğlu, İ., Altaş, İ.H.: The Effects of the Number of Rules on the Output of a Fuzzy Logic Controller Employed to a PMDC Motor. Computer & Electrical Engineering 24, 245–261 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Özen, A., Kaya, İ., Soysal, B. (2007). Design of a Fuzzy Based Outer Loop Controller for Improving the Training Performance of LMS Algorithm. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_118
Download citation
DOI: https://doi.org/10.1007/978-3-540-74282-1_118
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74281-4
Online ISBN: 978-3-540-74282-1
eBook Packages: Computer ScienceComputer Science (R0)