Performance analysis of the conventional complex LMS and augmented complex LMS algorithms

Recently, the augmented complex LMS (ACLMS) algorithm has been proposed for modeling complex-valued signal relationships in which a widely-linear model can be more appropriate. It is not clear, however, how the behavior of ACLMS differs from that of the conventional complex LMS (CCLMS) algorithm. In...

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Bibliographic Details
Published in2010 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 3794 - 3797
Main Authors Douglas, Scott C, Mandic, Danilo P
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2010
Subjects
Adaptive arrays
adaptive filters
adaptive signal processing
adaptive systems
Algorithm design and analysis
Array signal processing
Convergence
Covariance matrix
Independent component analysis
least mean square methods
Least squares approximation
Performance analysis
Signal analysis
Signal processing algorithms
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ISBN9781424442959
1424442958
ISSN1520-6149
DOI10.1109/ICASSP.2010.5495851

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Summary:Recently, the augmented complex LMS (ACLMS) algorithm has been proposed for modeling complex-valued signal relationships in which a widely-linear model can be more appropriate. It is not clear, however, how the behavior of ACLMS differs from that of the conventional complex LMS (CCLMS) algorithm. In this paper, we leverage a recently-developed analysis for the complex LMS algorithm to illuminate the performance relationships between the ACLMS and CCLMS algorithms. Our analysis shows that the ACLMS algorithm can potentially achieve a lower steady-state mean-squared error as compared to that of CCLMS, but the convergence speed of ACLMS is slowed in the presence of highly non-circular complex-valued input signals. An adaptive beamforming example indicates the utility of the results.
ISBN:9781424442959
1424442958
ISSN:1520-6149
DOI:10.1109/ICASSP.2010.5495851