Carrier Frequency Offset Estimation using Data-Dependent Superimposed Training

Moosvi, S. M. A.; McLernon, Des; Orozco-Lugo, A.G.; Lara, M.; Ghogho, Mounir

doi:10.1109/lcomm.2008.071822

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…Several studies on DDST suitability for time and frequency synchronization have been performed, e.g., [16,17], where it has been shown that DDST is also a viable solution for low SNR synchronization. We can present the channel between transmitter and receiver as an r times oversampled discrete-time equivalent channel, h eq (n) = |h RRC (t) ○ h channel (t) ○ h RRC (t)| t=nT/r = | h RRC ○ h channel+RRC | t=nT/r .…”

Section: System Modelmentioning

confidence: 99%

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

Levanen

Talvitie

Renfors

2012

J Wireless Com Network

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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.

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Section: System Modelmentioning

confidence: 99%

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

Levanen

Talvitie

Renfors

2012

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…In fact, (26) is estimated over multiple OFDM symbols with a weighted average function Compared with the conventional ST strategies, the proposed channel estimation is composed of two steps: First, with specially designed ST signals in (15) and (16), channel estimation can be reduced into that of LTI channel, and we are allowed to estimate the channel coefficients during each OFDM symbol as temporal results. Second, the temporal channel estimates are further enhanced over multiple OFDM symbols by using a weighted average procedure.…”

Section: Channel Estimation Over Multiple Ofdm Symbolsmentioning

confidence: 99%

“…In the latest contributions, J. K. Tugnait [16] extended the conventional ST to time-varying environment where the LTV channels are modeled by complex exponential bases. For the issue of training power allocation, the optimal pilot power has been investigated by [24] for different taps of low-pass filter, and then, the optimization of ST power allocation for LTI channel is mathematically analyzed based on equalizer design [15] [19].…”

Section: Introductionmentioning

confidence: 99%