A Constrained Reference Signal Based Beamformer Based on Symmetrically Distributed Antenna Arrays

Zhang, L., Liu, W. and Langley, R. J. (2010) A Constrained Reference Signal Based Beamformer Based on Symmetrically Distributed Antenna Arrays. In: 2010 Loughborough Antennas Propagation Conference, Loughborough, UK, 08-09 Nov 2010, pp. 121-124. ISBN 9781424473076 (doi:10.1109/LAPC.2010.5666788)

Zhang, L., Liu, W. and Langley, R. J. (2010) A Constrained Reference Signal Based Beamformer Based on Symmetrically Distributed Antenna Arrays. In: 2010 Loughborough Antennas Propagation Conference, Loughborough, UK, 08-09 Nov 2010, pp. 121-124. ISBN 9781424473076 (doi:10.1109/LAPC.2010.5666788)

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Abstract

A class of reference signal based (RSB) beamforming algorithms is proposed based on a symmetrically distributed array (SDA) by constraining its weight vector to a specific conjugate symmetric form, which is derived from the beamformer with a minimum mean square error (MSE). The effect of the additional constraint is equivalent to adding a second step in the derived adaptive algorithms. Moreover, since no direction of arrival (DOA) information of the desired signal is available, it leads to a two-stage structure for incorporating the imposed constraint. Compared to the traditional algorithms, the proposed ones, including an LMS (least mean square) based algorithm and an RLS (recursive least square) based algorithm, can achieve a faster convergence speed and a lower steady state mean square error (MSE), given the same stepsize.

Item Type:Conference Proceedings
Keywords:Antenna arrays, array signal processing, convergence, least mean squares methods, convergence speed, least mean square based algorithm, minimum mean square error, recursive least square based algorithm, reference signal based beamforming algorithm, symmetrically distributed antenna array, two-stage structure, weight vector, cost function, equations, signal to noise ratio.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Zhang, Dr Lei
Authors: Zhang, L., Liu, W., and Langley, R. J.
College/School:College of Science and Engineering > School of Engineering
ISBN:9781424473076

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