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Recursive least squares semi-blind beamforming for MIMO using decision directed adaptation and constant modulus criterion

Hong, X. and Chen, S. (2017) Recursive least squares semi-blind beamforming for MIMO using decision directed adaptation and constant modulus criterion. International Journal of Automation and Computing, 14 (4). pp. 442-449. ISSN 1476-8186

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To link to this item DOI: 10.1007/s11633-017-1087-6

Abstract/Summary

A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output (MIMO) induced and space- division multiple-access based wireless systems that employ high order phase shift keying signaling. A minimum number of training symbols, very close to the number of receiver antenna elements, are used to provide a rough initial least squares estimate of the beamformer0s weight vector. A novel cost function combining the constant modulus criterion with decision-directed adaptation is adopted to adapt the beamformer weight vector. This cost function can be approximated as a quadratic form with a closed-form solution, based on which we then derive the recursive least squares (RLS) semi-blind adaptive beamforming algorithm. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study. Our proposed semi-blind RLS beamforming algorithm therefore provides an e±cient detection scheme for the future generation of MIMO aided mobile communication systems.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:72077
Publisher:Springer

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