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Carrier Frequency Recovery for Nyquist and Faster-than-Nyquist Signaling System

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Abstract

Proposed is a new estimator for the carrier frequency recovery in Nyquist and faster-than-Nyquist (FTN) signaling system. Considering the intentional inter-symbol interference caused by FTN, a discrete-time model for synchronization of FTN is built for the first time, which is different from the traditional model based on the Nyquist criterion. The discrete-time model is simplified assumed that the frequency offset is much smaller than the sampling rate and the shaping pulse is time-truncated adopted from the 3GPP standard. Furthermore, a novel frequency estimator with three discrete Fourier transform samples interpolation is proposed for FTN signaling over the additive white Gaussian noise channel. Comparing with the Cramer–Rao bound, numerical results show the performance of new frequency estimator in the transmission system with the Nyquist rate and beyond the Nyquist rate.

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References

  1. Anderson, J. B., Rusek, F., & Owall, V. (2013). Faster-than-Nyquist signaling. IEEE Proceedings, 101(8), 1817–1830.

    Article  Google Scholar 

  2. Banelli, P., Buzzi, S., Colavolpe, G., Modenini, A., Rusek, F., & Ugolini, A. (2014). Modulation formats and waveforms for 5G networks: Who will be the heir of OFDM?: An overview of alternative modulation schemes for improved spectral efficiency. IEEE Signal Processing Magazine, 31(6), 80–93.

    Article  Google Scholar 

  3. Mazo, J. E. (1975). Faster-than-Nyquist signaling. Bell System Technical Journal, 54, 1451–1462.

    Article  MathSciNet  MATH  Google Scholar 

  4. Liveris, A. D., & Georghiades, C. N. (2003). Exploiting faster-than-Nyquist signaling. IEEE Transactions Communications, 51(9), 1502–1511.

    Article  Google Scholar 

  5. Modenini, A., Rusek, F., & Colavolpe, G. (2013). Optimal transmit filters for ISI channels under channel shortening detection. IEEE Transactions Communications, 61(12), 4997–5005.

    Article  Google Scholar 

  6. Beidas, B. F., Seshadri, R. I., Eroz, M., & Lee, L.-N. (2014). Faster-than-Nyquist signaling and optimized signal constellation for high spectral efficiency communications in nonlinear satellite systems. IEEE Military Communications Conference, 10(11), 818–823.

    Google Scholar 

  7. Prlja, A., & Anderson, J. B. (2012). Reduced-complexity receivers for strongly narrowband intersymbol interference introduced by faster-than-Nyquist signaling. IEEE Transaction Communication, 60(9), 2591–2601.

    Article  Google Scholar 

  8. Emil, R., (2013). Low complexity algorithms for faster-than-Nyquist signaling. Master of Science Thesis, School of Engineering Sciences, Royal Institute of Technology.

  9. Dasalukunte, D., Owall, V., Rusek, F., & Anderson, J. B. (2014). Faster than Nyquist signaling-algorithn to silicon. Berlin: Springer.

    Book  Google Scholar 

  10. Kay, S. (1989). A fast and accuracy single frequency estimator. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37(12), 1987–1990.

    Article  Google Scholar 

  11. Fitz, M. P, (1991). Planar filtered techniques for burst mode carrier sychronization. In Conf. Rec. GLOBECOM’91 (pp. 365–369).

  12. Luise, M., & Reggiannini, R. (1995). Carrier frequency recovery in all-digital modems for burst-mode transmissions. IEEE Transactions on Communications, 43(2–4), 1169–1178.

    Article  Google Scholar 

  13. Macleod, M. D. (1998). Fast nearly ML estimation of the parameters of real or complex single tones or resolved multiple tones. IEEE Transaction on Signal Processing, 46(1), 141–148.

    Article  Google Scholar 

  14. Quinn, B. G. (1994). Estimating frequency by interpolation using Fourier coefficients. IEEE Transaction on Signal Processing, 42(5), 1264–1268.

    Article  Google Scholar 

  15. Quinn, B. G. (1997). Estimation of frequency, amplitude, and phase from the DFT of a time series. IEEE Transaction on Signal Processing, 45(3), 814–817.

    Article  Google Scholar 

  16. Aboutanios, E., & Mulgrew, B. (2005). Iterative frequency estimation by interpolation on Fourier coefficients. IEEE Transaction on Signal Processing, 53(4), 1237–1242.

    Article  MathSciNet  Google Scholar 

  17. Liao, J. R., & Chen, C. M. (2014). Phase correction of discrete Fourier transform coefficients to reduce frequency estimation bias of single tone complex sinusoid. Signal Processing, 94, 108–117.

    Article  Google Scholar 

  18. Jacobsen, E., & Kootsookos, P. (2007). Fast, accurate frequency estimators. IEEE Transactions on Signal Processing, 24(3), 123–125.

    Article  Google Scholar 

  19. Candan, C. (2011). A method for fine resolution frequency estimation from three DFT samples. IEEE Signal Processing Letters, 18(6), 351–354.

    Article  Google Scholar 

  20. Candan, C. (2013). Analysis and further improvement of fine resolution frequency estimation method from three DFT samples. IEEE Signal Processing Letters, 20(9), 913–916.

    Article  Google Scholar 

  21. Liao, J. R., & Lo, S. (2014). Analytical solutions for frequency estimators by interpolation of DFT coefficients. Signal Processing, 100, 93–100.

    Article  Google Scholar 

  22. Technical Specification Group Radio Access Network, “Base station (BS) radio transmission and reception (FDD) (release 12),” 3GPP TS 25.104 V12.0.0 (2013-07). http://www.3gpp.org/ftp/Specs/archive/25series/25.104/.

  23. Mazzenga, F., & Corazza, G. (1998). Blind least-squares estimation of carrier phase, Doppler shift, Doppler rate for M-PSK burst transmission. IEEE Transaction Letters, 2(3), 73–75.

    Google Scholar 

  24. Kay, S. M. (1993). Fundamentals of statistical signal processing: Estimation theory (1st ed.). Englewood Cliffs, NJ: Prentice-Hall.

    MATH  Google Scholar 

Download references

Acknowledgements

The authors would like to thank all the anonymous reviewers for their constructive comments and suggestions which are helpful to improve the paper.

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Authors and Affiliations

  1. Key Laboratory of Military Satellite Communications, College of Communications Engineering, PLAUST, Nanjing, 210007, China

    X. H. Liang, A. J. Liu, X. F. Pan, F. Chen & Q. S. Zhang

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  1. X. H. Liang
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  2. A. J. Liu
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  3. X. F. Pan
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  4. F. Chen
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Correspondence to X. H. Liang.

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Liang, X.H., Liu, A.J., Pan, X.F. et al. Carrier Frequency Recovery for Nyquist and Faster-than-Nyquist Signaling System. Wireless Pers Commun 96, 4661–4673 (2017). https://doi.org/10.1007/s11277-017-4409-7

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  • DOI: https://doi.org/10.1007/s11277-017-4409-7

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