Channel Estimation Method for OFDM in Low SNR Based on Two-dimensional Spreading

Blumenstein, Jiří; Mars̆álek, Roman; Fedra, Zbynek; Prokeš, Aleš; Mecklenbräuker, Christoph F.

doi:10.1007/s11277-014-1779-y

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…5. MSE of selected channel estimators (in color), adopted from [32] together with fitted LMMSE with ideal CM as the best case estimator and hypothetically the worst case estimator as a combination of the LS estimator and 2D spreading estimator.…”

Section: Gfdm Modulation and Demodulationmentioning

confidence: 99%

“…The numerical value of MSE depends on the channel estimator and Signal to Noise Ratio (SNR). For several typical estimators, we have adopted the MSE curves as a function of SNR [32], see Fig. 5.…”

Section: Model Of the Equalizer Errormentioning

confidence: 99%

“…The LMMSE channel estimator with an ideal covariance matrix represents one of the best estimators. As the worst case estimator, we considered a combination of the least squares (LS, for SINR < 14.2 dB) and 2D spreading-based (for SINR > 14.2 dB), [32] estimators with MSE curves shown in Fig. 5.…”

Section: Evaluation By Simulationmentioning

confidence: 99%

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Adjacent Channel Interference Cancellation in FDM Transmissions

Harvanek

Mars̆álek

Kral

et al. 2020

IEEE Trans. Circuits Syst. I

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Interference between users in adjacent channels negatively affects throughput of mobile networks. In this paper we aim at cancellation of interference caused by a nonlinear power amplifier in a generalized orthogonal frequency division system. We propose an interference cancellation method to subtract these out-of-band emissions from the received signal. In contrast to state-of-the-art methods, our proposed method employs over-the-air estimation of power amplifier model parameters together with a particular frequency domain filtering method that allows to generate the required training data. The proposed interference cancellation method is also verified by an experiment on a software defined radio test bench.

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Section: Gfdm Modulation and Demodulationmentioning

confidence: 99%

Section: Model Of the Equalizer Errormentioning

confidence: 99%