| MI-NLMS adaptive beamforming algorithm for smart antenna system applications |
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| 作者姓名： | MOHAMMAD Tariqul Islam ZAINOL Abidin Abdul Rashid |
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| 作者单位： | Department of Electrical Electronics and System Engineering Faculty of Engineering Universiti Kebangsaan Malaysia，43600 Bangi Selangor D.E. Malaysia，Department of Electrical Electronics and System Engineering Faculty of Engineering Universiti Kebangsaan Malaysia，43600 Bangi Selangor D.E. Malaysia |
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| 基金项目： | Project supported by the IRPA Secretariat, Ministry of Science,Technology and Environment of Malaysia (No. 04-02-02-0029) andthe Zamalah Scheme |
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| 摘 要： | INTRODUCTION The demand for mobile communication services is increasing at a rapid pace throughout the globe. The increasing demand for mobile communication ser- vices in a limited RF spectrum motivates the need for better techniques to improve spectrum utilization. Smart antenna system was adopted by ITU for the IMT-2000 or the Third Generation (3G) wireless networks due to its capability to improve channel capacity and interference suppression. A smart an- tenna system combines mult…
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| 关 键 词： | 智能天线 LMS NLMS MI-NLMS 移动通信 |
| 收稿时间： | 2006-06-14 |
| 修稿时间： | 2006-07-12 |
MI-NLMS adaptive beamforming algorithm for smart antenna system applications |
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| MOHAMMAD Tariqul Islam ZAINOL Abidin Abdul Rashid.MI-NLMS adaptive beamforming algorithm for smart antenna system applications[J].Journal of Zhejiang University Science,2006,7(10):1709-1716. |
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| Authors: | Tariqul Islam Mohammad Abidin Abdual Rashid Zainol |
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| Institution: | (1) Department of Electrical, Electronics and System Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor D.E., Malaysia |
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| Abstract: | 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. |
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| Keywords: | Smart antenna Beamforming algorithm Least Mean Square (LMS) Normalized LMS (NLMS) Matrix Inversion NLMS (MI-NLMS) |
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