A Review of Fixed-Complexity Vector Perturbation for MU-MIMO


Manar Mohaisen, Journal of Information Processing Systems Vol. 11, No. 3, pp. 354-369, Jun. 2015  

10.3745/JIPS.03.0035
Keywords: Block Diagonalization, MU-MIMO, Perfect and Imperfect Channel Knowledge, Quantization, Vector Perturbation
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Abstract

Recently, there has been an increasing demand of high data rates services, where several multiuser multiple- input multiple-output (MU-MIMO) techniques were introduced to meet these demands. Among these tech- niques, vector perturbation combined with linear precoding techniques, such as zero-forcing and minimum mean-square error, have been proven to be efficient in reducing the transmit power and hence, perform close to the optimum algorithm. In this paper, we review several fixed-complexity vector perturbation techniques and investigate their performance under both perfect and imperfect channel knowledge at the transmitter. Also, we investigate the combination of block diagonalization with vector perturbation outline its merits.


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Cite this article
[APA Style]
Manar Mohaisen (2015). A Review of Fixed-Complexity Vector Perturbation for MU-MIMO. Journal of Information Processing Systems, 11(3), 354-369. DOI: 10.3745/JIPS.03.0035.

[IEEE Style]
M. Mohaisen, "A Review of Fixed-Complexity Vector Perturbation for MU-MIMO," Journal of Information Processing Systems, vol. 11, no. 3, pp. 354-369, 2015. DOI: 10.3745/JIPS.03.0035.

[ACM Style]
Manar Mohaisen. 2015. A Review of Fixed-Complexity Vector Perturbation for MU-MIMO. Journal of Information Processing Systems, 11, 3, (2015), 354-369. DOI: 10.3745/JIPS.03.0035.