Low-Complexity Robust Adaptive Beamforming Based on Shrinkage and Cross-Correlation

Conference: WSA 2015 - 19th International ITG Workshop on Smart Antennas
03/03/2015 - 03/05/2015 at Ilmenau, Deutschland

Proceedings: WSA 2015

Pages: 5Language: englishTyp: PDF

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Authors:
Ruan, Hang; Lamare, Rodrigo C. de (Department of Electronics, The University of York, YO10 5BB, England)
Lamare, Rodrigo C. de (CETUC, Pontifical Catholic University of Rio de Janeiro, Brazil)

Abstract:
In this paper, we propose a low-complexity robust adaptive beamforming (RAB) technique based on shrinkage and cross-correlation methods. We firstly review a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) method which estimates the desired signal steering vector mismatch and the desired signal power. We then develop low-cost stochastic gradient recursions to estimate the INC matrix and update the beamforming weights, rather than directly computing the beamforming weights with matrix inversions as in LOCSME, resulting in the proposed LOCSME-SG algorithm. Simulations show that LOCSME-SG achieves excellent output signal-to-interference-plus-noise ratio performance compared to previously reported adaptive RAB algorithms.