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Performance evaluation of time-multiplexed and data-dependent superimposed training based transmission with practical power amplifier model

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Performance evaluation of time-multiplexed and data-dependent superimposed training based transmission with practical power amplifier model. / Levanen, Toni; Talvitie, Jukka; Renfors, Markku.

julkaisussa: Eurasip Journal on Wireless Communications and Networking, Vuosikerta 2012, Nro 1, 49, 2012, s. 1-19.

Tutkimustuotosvertaisarvioitu

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Levanen, T, Talvitie, J & Renfors, M 2012, 'Performance evaluation of time-multiplexed and data-dependent superimposed training based transmission with practical power amplifier model', Eurasip Journal on Wireless Communications and Networking, Vuosikerta. 2012, Nro 1, 49, Sivut 1-19. https://doi.org/10.1186/1687-1499-2012-49

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Levanen, Toni ; Talvitie, Jukka ; Renfors, Markku. / Performance evaluation of time-multiplexed and data-dependent superimposed training based transmission with practical power amplifier model. Julkaisussa: Eurasip Journal on Wireless Communications and Networking. 2012 ; Vuosikerta 2012, Nro 1. Sivut 1-19.

Bibtex - Lataa

@article{f83c4e25076146f1964d3d523c3bc3d0,
title = "Performance evaluation of time-multiplexed and data-dependent superimposed training based transmission with practical power amplifier model",
abstract = "The increase in the peak-to-average power ratio (PAPR) is a well known but not sufficiently addressed problem with data-dependent superimposed training (DDST) based approaches for channel estimation and synchronization in digital communication links. In this article, we concentrate on the PAPR analysis with DDST and on the spectral regrowth with a nonlinear amplifier. In addition, a novel Gaussian distribution model based on the multinomial distribution for the cyclic mean component is presented. We propose the use of a symbol level amplitude limiter in the transmitter together with a modified channel estimator and iterative data bit estimator in the receiver. We show that this setup efficiently reduces the regrowth with the DDST. In the end, spectral efficiency comparison between time domain multiplexed training and DDST with or without symbol level limiter is provided. The results indicate improved performance for DDST based approaches with relaxed transmitter power amplifier requirements.",
author = "Toni Levanen and Jukka Talvitie and Markku Renfors",
note = "Contribution: organisation=tlt,FACT1=1<br/>Publisher name: Springer",
year = "2012",
doi = "10.1186/1687-1499-2012-49",
language = "English",
volume = "2012",
pages = "1--19",
journal = "Eurasip Journal on Wireless Communications and Networking",
issn = "1687-1472",
publisher = "Springer Verlag",
number = "1",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Performance evaluation of time-multiplexed and data-dependent superimposed training based transmission with practical power amplifier model

AU - Levanen, Toni

AU - Talvitie, Jukka

AU - Renfors, Markku

N1 - Contribution: organisation=tlt,FACT1=1<br/>Publisher name: Springer

PY - 2012

Y1 - 2012

N2 - The increase in the peak-to-average power ratio (PAPR) is a well known but not sufficiently addressed problem with data-dependent superimposed training (DDST) based approaches for channel estimation and synchronization in digital communication links. In this article, we concentrate on the PAPR analysis with DDST and on the spectral regrowth with a nonlinear amplifier. In addition, a novel Gaussian distribution model based on the multinomial distribution for the cyclic mean component is presented. We propose the use of a symbol level amplitude limiter in the transmitter together with a modified channel estimator and iterative data bit estimator in the receiver. We show that this setup efficiently reduces the regrowth with the DDST. In the end, spectral efficiency comparison between time domain multiplexed training and DDST with or without symbol level limiter is provided. The results indicate improved performance for DDST based approaches with relaxed transmitter power amplifier requirements.

AB - The increase in the peak-to-average power ratio (PAPR) is a well known but not sufficiently addressed problem with data-dependent superimposed training (DDST) based approaches for channel estimation and synchronization in digital communication links. In this article, we concentrate on the PAPR analysis with DDST and on the spectral regrowth with a nonlinear amplifier. In addition, a novel Gaussian distribution model based on the multinomial distribution for the cyclic mean component is presented. We propose the use of a symbol level amplitude limiter in the transmitter together with a modified channel estimator and iterative data bit estimator in the receiver. We show that this setup efficiently reduces the regrowth with the DDST. In the end, spectral efficiency comparison between time domain multiplexed training and DDST with or without symbol level limiter is provided. The results indicate improved performance for DDST based approaches with relaxed transmitter power amplifier requirements.

U2 - 10.1186/1687-1499-2012-49

DO - 10.1186/1687-1499-2012-49

M3 - Article

VL - 2012

SP - 1

EP - 19

JO - Eurasip Journal on Wireless Communications and Networking

JF - Eurasip Journal on Wireless Communications and Networking

SN - 1687-1472

IS - 1

M1 - 49

ER -