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Efficient linear precoding for massive MIMO systems using truncated polynomial expansion
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Alcatel-Lucent Department on Flexible Radio, Supélec, France .
2014 (English)In: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, 2014, 273-276 p.Conference paper (Refereed)
Abstract [en]

Massive multiple-input multiple-output (MIMO) techniques have been proposed as a solution to satisfy many requirements of next generation cellular systems. One downside of massive MIMO is the increased complexity of computing the precoding, especially since the relatively 'antenna-efficient' regularized zero-forcing (RZF) is preferred to simple maximum ratio transmission. We develop in this paper a new class of precoders for single-cell massive MIMO systems. It is based on truncated polynomial expansion (TPE) and mimics the advantages of RZF, while offering reduced and scalable computational complexity that can be implemented in a convenient parallel fashion. Using random matrix theory we provide a closed-form expression of the signal-to-interference-and-noise ratio under TPE precoding and compare it to previous works on RZF. Furthermore, the sum rate maximizing polynomial coefficients in TPE precoding are calculated. By simulation, we find that to maintain a fixed peruser rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and signal-to-noise ratio.

Place, publisher, year, edition, pages
2014. 273-276 p.
, Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, ISSN 2151-870X ; 6882393
Keyword [en]
MIMO systems, Random variables, Signal to noise ratio, Closed-form expression, Maximum ratio transmission, Multiple input multiple output techniques, Polynomial coefficients, Polynomial degree, Polynomial expansion, Random matrix theory, Signal-to-interference and noise ratios, Signal processing
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-167547DOI: 10.1109/SAM.2014.6882394ISI: 000360273100069ScopusID: 2-s2.0-84906247357ISBN: 9781479914814OAI: diva2:818592
2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014, 22 June 2014 through 25 June 2014, A Coruna

QC 20150609

Available from: 2015-06-09 Created: 2015-05-22 Last updated: 2015-09-18Bibliographically approved

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Björnson, Emil
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