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Constrained Least Mean Square Algorithm with Coefficient Reusing

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Abstract

The constrained least mean square (CLMS) algorithm is one of the most popular online linear-equality-constrained beamforming algorithms. This paper demonstrates for the first time that it solves a deterministic minimum-disturbance optimization problem in an exact manner. Such a framework is employed to insert the coefficient reusing technique into the algorithm, engendering a new low-complexity constrained adaptive filter, designated as RC-CLMS, that trades convergence rate for asymptotic performance. A stochastic model that predicts the average evolution of adaptive weights is derived. Through simulations, the advanced reusing coefficient extension of the constrained least mean-square algorithm enhanced the asymptotic signal-to-interference-plus-noise ratio and decreased the steady-state mean output energy. Furthermore, the resulting beam pattern is analyzed with an antenna analysis tool, confirming the efficacy of the advanced algorithm in a realistic setting, when the electromagnetic coupling between the antennas is taken into account.

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Acknowledgements

This work was partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES) Finance Code 001 and by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ).

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Authors and Affiliations

  1. Centro Federal de Educação Tecnológica Celso Suckow da Fonseca, Rio de Janeiro, RJ, Brazil

    Valmir S. Nogueira Junior, Maurício H. C. Dias & Diego B. Haddad

  2. Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ, Brazil

    Michel P. Tcheou

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  1. Valmir S. Nogueira Junior
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  2. Michel P. Tcheou
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  3. Maurício H. C. Dias
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  4. Diego B. Haddad
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Correspondence to Diego B. Haddad.

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Junior, V.S.N., Tcheou, M.P., Dias, M.H.C. et al. Constrained Least Mean Square Algorithm with Coefficient Reusing. Circuits Syst Signal Process 40, 5705–5717 (2021). https://doi.org/10.1007/s00034-021-01721-w

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