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International Journal of Electrical and Computer Engineering Systems, Vol. 14 No. 8, 2023.

Original scientific paper

https://doi.org/10.32985/ijeces.14.8.1

Beamforming Array Antenna Technique Based on Partial Update Adaptive Algorithms

Zahraa A. Shubber ; University of Technology- Iraq Department of Electrical and Electronics Engineering Baghdad, Iraq
Thamer M. Jamel orcid id orcid.org/0000-0002-6555-7243 ; University of Technology- Iraq Department of Communications Engineering Baghdad, Iraq
Ali. K. Nahar orcid id orcid.org/0000-0002-6301-0447 ; University of Technology- Iraq Department of Electrical and Electronics Engineering Baghdad, Iraq

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Abstract

The most important issues for improving the performance of modern wireless communication systems are interference cancellation, efficient use of energy, improved spectral efficiency and increased system security. Beamforming Array Antenna (BAA) is one of the efficient methods used for this purpose. Full band BAA, on the other hand, will suffer from a large number of controllable elements, a long convergence time and the complexity of the beamforming network. Since no attempt had previously been made to use Partial Update (PU) for BAA, the main novelty and contribution of this paper was to use PU instead of full band adaptive algorithms. PU algorithms will connect to a subset of the array elements rather than all of them. As a result, a common number of working antennas for the system's entire cells can be reduced to achieve overall energy efficiency and high cost-effectiveness. In this paper, we propose a new architectural model that employs PU adaptive algorithms to control and minimize the number of phase shifters, thereby reducing the number of base station antennas. We will concentrate on PU LMS (Least Mean Square) algorithms such as sequential-LMS, M-max LMS, periodic-LMS, and stochastic-LMS. According to simulation results using a Uniform Linear Array (ULA) and three communications channels, the M-max-LMS, periodic LMS, and stochastic LMS algorithms perform similarly to the full band LMS algorithm in terms of square error, tracking weight coefficients, and estimation input signal, with a quick convergence time, low level of error signal at steady state and keeping null steering's interference-suppression capability intact.

Keywords

Beamforming Array Antenna; Partial Update Adaptive Algorithm; Full band LMS; M-max PU LMS; sequential PU LMS; periodic PU LMS and stochastic PU LMS algorithms;

Hrčak ID:

309134

URI

https://hrcak.srce.hr/309134

Publication date:

23.10.2023.

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