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Received: 2006-06-14

Revision Accepted: 2006-07-12

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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.10 P.1709-1716


MI-NLMS adaptive beamforming algorithm for smart antenna system applications

Author(s):  MOHAMMAD Tariqul Islam, ZAINOL Abidin Abdul Rashid

Affiliation(s):  Department of Electrical, Electronics and System Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor D.E., Malaysia

Corresponding email(s):   titareq@yahoo.com, zaar@vlsi.eng.ukm.my

Key Words:  Smart antenna, Beamforming algorithm, Least Mean Square (LMS), Normalized LMS (NLMS), Matrix Inversion NLMS (MI-NLMS)

MOHAMMAD Tariqul Islam, ZAINOL Abidin Abdul Rashid. MI-NLMS adaptive beamforming algorithm for smart antenna system applications[J]. Journal of Zhejiang University Science A, 2006, 7(10): 1709-1716.

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T1 - MI-NLMS adaptive beamforming algorithm for smart antenna system applications
A1 - MOHAMMAD Tariqul Islam
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J0 - Journal of Zhejiang University Science A
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DOI - 10.1631/jzus.2006.A1709

A Matrix Inversion Normalized Least Mean Square (MI-NLMS) adaptive beamforming algorithm was developed for smart antenna application. The MI-NLMS which combined the individual good aspects of Sample Matrix Inversion (SMI) and the Normalized Least Mean Square (NLMS) algorithms is described. Simulation results showed that the less complexity MI-NLMS yields 15 dB improvements in interference suppression and 5 dB gain enhancement over LMS algorithm, converges from the initial iteration and achieves 24% BER improvements at cochannel interference equal to 5. For the case of 4-element uniform linear array antenna, MI-NLMS achieved 76% BER reduction over LMS algorithm.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1] Agee, B., 1989. Blind separation and capture of communication signals using a multitarget constant modulus beamformer. Proceedings of the IEEE Military Communications Conference, 2:340-346.

[2] Chen, S., Ahmad, N.N., Hanzo, L., 2005. Adaptive minimum bit-error rate beamforming. IEEE Transactions on Wireless Communications, 4(2):341-348.

[3] Ganz, M.W., Moses, R.L., Wilson, S.L., 1990. Convergence of the SMI and the diagonally loaded SMI algorithms with weak interference (adaptive array). IEEE Trans. Antennas Propagat., 38(3):394-399.

[4] Godara, L.C., 1997. Applications of antenna arrays to mobile communications. Part I: performance improvement, feasibility, and system considerations. Proc. IEEE, 85(7):1031-1060.

[5] Griffiths, L.J., 1969. A simple adaptive algorithm for real-time processing in antenna arrays. Proc. IEEE, 57:1696-1704.

[6] Haykin, S., 1996. Adaptive Filter Theory (3rd Ed.). Prentice Hall, New York.

[7] Islam, M.T., Ping, C.C., Rashid, Z.A.A., 2003. Performance Evaluation of Adaptive Non-blind Algorithms of a Digital Beamforming System for Linear Array Antenna. The 6th International Conference on Computer & Information Technology. Dhaka, Bangladesh, p.686-691.

[8] Krim, H., Viberg, M., 1996. Two decades of array signal processing research: the parametric approach. IEEE Signal Processing Magazine, 13(4):67-94.

[9] Liberti, J.C., Rappapoert, T.S., 2002. Smart Antenna for Wireless Communications Is-95 and Third Generation CDMA Applications. Prentice-Hall PTR, New Jersey.

[10] Litva, J., Lo, T.K.Y., 1996. Digital Beamforming in Wireless Communications. Artech, London, U.K.

[11] Reed, I.S., Mallett, J.D., Brennan, L.E., 1974. Rapid convergence rate in adaptive arrays. IEEE Trans. Aerosp. Electron. Syst., 10:853-863.

[12] Wells, M.C., 1996. Increasing the capacity of GSM cellular radio using adaptive antennas. IEE Proc. Comm., 143(5):304-310.

[13] Widrow, B., Mantey, P.E., Griffiths, L.J., Goode, B.B., 1967. Adaptive antenna systems. Proc. IEEE, 55:2143-2159.

[14] Yasui, Y., Kobaysakawa, S., Nakamura, T., 2002. Adaptive array antenna for W-CDMA systems. FUJITSU Sci. Tech. J., 38(2):192-200.

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