A class of constant modulus algorithms for uniform linear arrays with a conjugate symmetric constraint

• Published in: Signal processing Vol. 90; no. 9; pp. 2760 - 2765
• Main Authors: Zhang, Lei, Liu, Wei, Langley, Richard J.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.09.2010; Elsevier
• Subjects: Algorithms; Applied sciences; Blind beamforming; Conjugate symmetric; Conjugates; Constant modulus; Detection, estimation, filtering, equalization, prediction; Equivalence; Exact sciences and technology; Information, signal and communications theory; Least squares method; Linear arrays; Mathematical analysis; Optimization; Signal and communications theory; Signal, noise; Telecommunications and information theory; Uniform linear arrays; Weight reduction; Blind beamforming; Conjugate symmetric; Constant modulus; Uniform linear arrays; Performance evaluation; Adaptive algorithm; Updating; Output signal; Beam forming; Constant modulus algorithm; Least squares method; Linear antenna arrays; Signal to interference plus noise ratio
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2010.04.003

A class of constant modulus algorithms (CMAs) subject to a conjugate symmetric constraint is proposed for blind beamforming based on the uniform linear array structure. The constraint is derived from the beamformer with an optimum output signal-to-interference-plus-noise ratio (SINR). The effect of the additional constraint is equivalent to adding a second step to the original adaptive algorithms. The proposed approach is general and can be applied to both the traditional CMA and its all kinds of variants, such as the linearly constrained CMA (LCCMA) and the least squares CMA (LSCMA) as two examples. With this constraint, the modified CMAs will always generate a weight vector in the desired form for each update and the number of adaptive variables is effectively reduced by half, leading to a much improved overall performance.