Dual-Domain Adaptive Beamformer Under Linearly and Quadratically Constrained Minimum Variance

作者：Yukawa Masahiro^*; Sung Youngchul; Lee Gilwon

来源：IEEE Transactions on Signal Processing, 2013, 61(11): 2874-2886.

DOI：10.1109/TSP.2013.2254481

• Adaptive beamforming
• dual-domain adaptive algorithm
• LCMV
• LQCMV
• relaxed zero forcing

In this paper, a novel adaptive beamforming algorithm is proposed under a linearly and quadratically constrained minimum variance (LQCMV) beamforming framework, based on a dual-domain projection approach that can efficiently implement a quadratic-inequality constraint with a possibly rank-deficient positive semi-definite matrix, and the properties of the proposed algorithm are analyzed. As an application, relaxed zero-forcing (RZF) beamforming is presented which adopts a specific quadratic constraint that bounds the power of residual interference in the beamformer output with the aid of interference-channel side-information available typically in wireless multiple-access systems. The dual-domain projection in this case plays a role in guiding the adaptive algorithm towards a better direction to minimize the interference and noise, leading to considerably faster convergence. The robustness issue against channel mismatch and ill-posedness is also addressed. Numerical examples show that the efficient use of interference side-information brings considerable gains.

• 出版日期2013-6