An adaptive LCMV beamforming algorithm based on dynamic selection of constraints

• Published in: 2010 7th International Symposium on Wireless Communication Systems pp. 404 - 407
• Main Authors: Rui Fa, de Lamare, Rodrigo C
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2010
• Subjects: Algorithm design and analysis; Array signal processing; Arrays; Complexity theory; Heuristic algorithms; Interference; Program processors
• ISBN: 9781424463152; 1424463157
• ISSN: 2154-0217
• DOI: 10.1109/ISWCS.2010.5624284

A novel approach to linearly constrained minimum variance (LCMV) beamforming based on dynamic selection of constraints (DSC) is proposed. The method employs a multiple parallel processors (MPP) framework, where each processor is optimized subject to a particular linear constraint. A selection criterion is employed at the output of the scheme to select the best processor for each time instant. We also present low-complexity stochastic gradient (SG) and recursive least squares (RLS) adaptive algorithms for the efficient implementation of the proposed scheme. Furthermore, a complexity analysis of the proposed and existing schemes in terms of the number of multiplications and additions is carried out. Simulations results with a uniform linear array (ULA) model show that the proposed scheme and algorithms significantly improve the performance of conventional LCMV beamforming.