Simulation of a smart antenna system

Simulation of a smart antenna system

Smart Antenna technologies will change the economics of 3G radio networks. They provide either a major data capacity gain or a significant reduction in the number of base stations required to achieve a base level of service. When deployed optimally, Smart Antennas can increase the capacity of a netw...

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Main Author: Rosli, Nur Alina Zureen
Format: Thesis
Language:English
Published: 2008
Subjects:
TK Electrical engineering
Electronics Nuclear engineering
HE Transportation and Communications
Online Access:http://eprints.utm.my/id/eprint/9668/1/NurAlinaZureenMFKE2008.pdf
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id my-utm-ep.9668
record_format uketd_dc
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic TK Electrical engineering
Electronics Nuclear engineering
HE Transportation and Communications
spellingShingle TK Electrical engineering
Electronics Nuclear engineering
HE Transportation and Communications
Rosli, Nur Alina Zureen
Simulation of a smart antenna system
description Smart Antenna technologies will change the economics of 3G radio networks. They provide either a major data capacity gain or a significant reduction in the number of base stations required to achieve a base level of service. When deployed optimally, Smart Antennas can increase the capacity of a network by more than 100% or reduce the required number of base stations to less than 50%. It is not surprising that Smart Antennas are more expensive than conventional technologies. These costs are a fraction on the gain achieved, but they mean that smart deployment will produce the most cost-effective result. This thesis is an overview of Smart Antenna technology, their benefits, how they work and how they can be deployed to best advantage. Implementation that revolves around the Least Mean Square (LMS) adaptive algorithm, chosen for its computational simplicity and high stability algorithm into the MATLAB® simulation of an adaptive array of a smart antenna base station system, is to investigate its performance in the presence of multipath components and multiple users. The simulations illustrate that adaptive array antenna systems are able to adjust their antenna pattern to enhance desired signals, and reduce interference.
format Thesis
qualification_level Master's degree
author Rosli, Nur Alina Zureen
author_facet Rosli, Nur Alina Zureen
author_sort Rosli, Nur Alina Zureen
title Simulation of a smart antenna system
title_short Simulation of a smart antenna system
title_full Simulation of a smart antenna system
title_fullStr Simulation of a smart antenna system
title_full_unstemmed Simulation of a smart antenna system
title_sort simulation of a smart antenna system
granting_institution Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department Faculty of Electrical Engineering
publishDate 2008
url http://eprints.utm.my/id/eprint/9668/1/NurAlinaZureenMFKE2008.pdf
_version_ 1747814772724727808
spelling my-utm-ep.96682018-07-23T05:36:42Z Simulation of a smart antenna system 2008-05 Rosli, Nur Alina Zureen TK Electrical engineering. Electronics Nuclear engineering HE Transportation and Communications Smart Antenna technologies will change the economics of 3G radio networks. They provide either a major data capacity gain or a significant reduction in the number of base stations required to achieve a base level of service. When deployed optimally, Smart Antennas can increase the capacity of a network by more than 100% or reduce the required number of base stations to less than 50%. It is not surprising that Smart Antennas are more expensive than conventional technologies. These costs are a fraction on the gain achieved, but they mean that smart deployment will produce the most cost-effective result. This thesis is an overview of Smart Antenna technology, their benefits, how they work and how they can be deployed to best advantage. Implementation that revolves around the Least Mean Square (LMS) adaptive algorithm, chosen for its computational simplicity and high stability algorithm into the MATLAB® simulation of an adaptive array of a smart antenna base station system, is to investigate its performance in the presence of multipath components and multiple users. The simulations illustrate that adaptive array antenna systems are able to adjust their antenna pattern to enhance desired signals, and reduce interference. 2008-05 Thesis http://eprints.utm.my/id/eprint/9668/ http://eprints.utm.my/id/eprint/9668/1/NurAlinaZureenMFKE2008.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering [1] L. C. Godara, Application of Antenna Arrays to Mobile Communications, Part I: Performance Improvement, Feasibility, and System Considerations, Proceedings of the IEEE, Vol. 85, No. 7, July 1997, pp. 1029-1060. [2] Wong, K.K., Murch, R.D. & Letaief, K.B. 2001. Optimizing Time and Space MIMO Antenna System for Frequency Selective Fading Channels. IEEE Journal on Selected Areas in Communications, July, pp.1395-1406. [3] Rappaport, T.S. 1996 Wireless Communications: Principles & Practice, Prentice Hall Communications Engineering and Emerging Technology Series. [4] Oeting, J. 1983. Cellular Mobile Radio — An Emerging Technology. IEEE Communications Magazine, November, pp. 10-15. [5] Rosol, G. 1995. Base Station Antennas: Part 1, Part 2, Part 3. Microwaves & RF, August, pp. 117-123, September, pp. 127-131, October, pp. 116-124. [6] Brickhouse, R.A., and Rappaport, T.S. 1997. A Simulation Study of Urban In- Building Frequency Reuse. IEEE Personal Communications Magazine, February, pp. 19-23. [7] Liberti, J. C. & Rappaport, T.S. 1999. Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA Applications, Prentice Hall Communications Engineering and Emerging Technology Series, NJ. [8] Haykin, S. 1996. Adaptive Filter Theory, Third Edition, Prentice Hall Inc., pp. 365 — 405. How, L. 2001. Signed LMS Adaptive Filtering with Detection. Undergraduate Thesis, School of Information Technology and Electrical Engineering, University of Queensland, Brisbane. [9] Pattan, B. 2000. Robust Modulation methods and Smart Antennas in Wireless Communications, Prentice Hall PTR, NJ. [10] Zooghby, A. 2001. Potentials of Smart Antennas in CDMA Systems and Uplink Improvements. IEEE Antennas and Propagation Magazine, pp. 172177. [11] Widrow, B., Mantey, P. E., Griffiths, L. J., and Goode, B. B. 1967. Adaptive Antenna Systems. Proc. of the IEEE, December. [12] Monzingo, R. & Miller, T. 1980. Introduction to Adaptive Arrays, Wiley and Sons, NY. [13] Frost, 0. L., III. 1972. An Algorithm for Linearly Constrained Adaptive Array Processing, Proc. of the IEEE, August. [14] Jing Jiang, R. Michael Buehrer, and William H. Tranter, Antenna Diversity in Multiuser Data Networks, IEEE Trans. Comm., vol. 52, no. 3, pp. 490-497, Mar. 2004. [15] Jeffrey H. Reed, Software Radio: A modern approach to radio engineering, Prentice Hall Communications Engineering and Emerging technology series 2002. [16] S. Choi and J. H. Reed, “Smart Antenna API,� a power point presentation submitted to Technical Committee SDRF, June 15, 2004.

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