A Minimum Variance Noise Algorithm for 2D and 3D Direction Estimation in MIMO Wireless Communication Systems

Al-Sadoon, M. A. G., Zweid, A., Asif, R., Bin-Melha, M. S., Abduljabbar, N., Noras, J. M. and Abd-Alhameed, R. A. (2019) A Minimum Variance Noise Algorithm for 2D and 3D Direction Estimation in MIMO Wireless Communication Systems. In: Proceedings - 2018 International Conference on Wireless Networks and Mobile Communications, WINCOM 2018. Proceedings - 2018 International Conference on Wireless Networks and Mobile Communications, WINCOM 2018 . Institute of Electrical and Electronics Engineers Inc., MAR. ISBN 9781538673300

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Abstract

Angle of arrival (AOA) estimation plays an essential role in several signal processing applications including tracking systems, beamforming technology and radar systems. An efficient AOA algorithm is proposed to find the direction of multiple arrival signal sources in 2D and 3D applications. The new method is called Minimum Variance Noise (MVN) and it depends upon the minimizing the output noise variance of an antenna array. The main idea and principal working of the MVN algorithm are presented and the mathematical model is derived. The Lagrange optimization technique is utilized to obtain the optimum weights. A computer simulation is carried out on linear and circular arrays including a wide range of scenarios to evaluate the estimation accuracy of the new algorithm. It is also compared with the popular AOA techniques and the results show that it gives better results with lower complexity.

Item Type: Book Section
Additional Information: Publisher Copyright: © 2018 IEEE.
Uncontrolled Keywords: angle of arrival (aoa),antenna array,minimum variance,positioning systems,wireless communication,computer networks and communications,communication ,/dk/atira/pure/subjectarea/asjc/1700/1705
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 23 Aug 2022 13:30
Last Modified: 22 Oct 2022 08:32
URI: https://ueaeprints.uea.ac.uk/id/eprint/87567
DOI: 10.1109/WINCOM.2018.8629717

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