Advertisement

Wireless Personal Communications

, Volume 97, Issue 3, pp 4813–4825 | Cite as

A Low-Complexity Hardware-Friendly DFT-Based Channel Estimator for the LTE Uplink Channel

  • Xiaoming DaiEmail author
  • Zhenyu Zhang
  • Linglong Dai
  • Baoming Bai
Article
  • 99 Downloads

Abstract

In this work, a low-complexity hardware-friendly discrete Fourier transform (DFT)-based channel estimator with almost no inherent “edge effect” is designed for the long-term evolution (LTE) uplink channel. Specifically, we propose to perform the border symmetric extension (BSE) operation on the border subcarriers of the channel frequency response (CFR), such that the length of the extended CFR fulfills \(2^{\lceil {{\text {log}}_2N}\rceil }\), where N denotes the non-radix-2 length of the original CFR, and \(\lceil {x}\rceil\) stands for the integer ceiling function. Based on the proposed BSE operation, the discontinuities at the CFR’s border subcarriers are significantly lessened and a better power concentration of the transform-domain channel impulse response is realized. As a result, the inherent “edge effect” caused by the virtual subcarriers in LTE systems can be substantially reduced. A further advantage of the proposed method is that the cumbersome application specific integrated circuit-based implementation of 34 different non-radix-2 length DFT/IDFT operations can be accomplished in a single structure by their fast Fourier transform and inverse fast Fourier transform counterparts. Numerical results illustrate that the proposed DFT-based channel estimator with BSE achieves significant performance gains over the conventional counterpart, despite imposing a reduced computational complexity.

Keywords

Application specific integrated circuit (ASIC) Border symmetric extension (BSE) Discrete Fourier transform (DFT) Edge effect Fast Fourier transform (FFT) 

References

  1. 1.
    Hsieh, M. H., & Wei, C. H. (1998). Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels. IEEE Transactions on Consumer Electronics, 44(1), 217–225.CrossRefGoogle Scholar
  2. 2.
    Edfors, O., Sandell, M., Beek, J. J., Wilson, S. K., & Borjesson, P. O. (1998). OFDM channel estimation by singular value decomposition. IEEE Transactions on Communications, 46(7), 931–939.CrossRefGoogle Scholar
  3. 3.
    Li, Y. (2000). Pilot-symbol-aided channel estimation for OFDM in wireless systems. IEEE Transactions on Vehicular Technology, 49(4), 1207–1215.CrossRefGoogle Scholar
  4. 4.
    Noh, M., Lee, Y., & Park, H. (2006). Low complexity LMMSE channel estimation for OFDM. IEEE Proceedings Communications, 153(5), 645–650.CrossRefGoogle Scholar
  5. 5.
    Zhang, Q. C., Zhu, X. D., Yang, T., & Liu, J. (2013). An enhanced DFT-based channel estimator for LTE-A uplink. IEEE Transactions on Vehicular Technology, 62(9), 4690–4696.CrossRefGoogle Scholar
  6. 6.
    Zhao, Y., & Huang, A. (May 1997) A novel channel estimation method for OFDM mobile communication systems based on pilot signals and transform-domain processing. In Proc. IEEE VTC, 97-spring (pp. 2089–2093).Google Scholar
  7. 7.
    3rd Generation Partnership Project, Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Multiplexing and channel coding, 3GPP TS. 36.212 V9.1.0 (Mar. 2010).Google Scholar
  8. 8.
    Edfors, O., Sandell, M., van de Beek, J.J., Wilson, S.K., & Borjesson, P.O. (2000). Analysis of DFT-based channel estimators for OFDM. Wireless Personal Communications, 12(1), 55–70.Google Scholar
  9. 9.
    Lin, Y. P., & Phoong, S.-M. (2005). Window designs for DFT-based multicarrier systems. IEEE Transactions on Signal Processing, 53(3), 1015–1024.MathSciNetCrossRefGoogle Scholar
  10. 10.
    Seo, J. W., Wee, J. W., Park, Y. S., Paik, J. H., & Jeon, W. G. (May 2005). DFT-based PSA channel estimation using linear prediction for OFDM systems with virtual subcarriers. In Proc. IEEE VTC, 05-spring (pp. 510–513).Google Scholar
  11. 11.
    Seo, J. W., Wee, J. W., Jeon, W. G., Paik, J. H., & Kim, D. K. (Sept. 2006). Enhanced DFT-based channel estimation using virtual interpolation with guard bands prediction for OFDM. In Proc. IEEE PIMRC 06.Google Scholar
  12. 12.
    3rd Generation Partnership Project, Study on provision of low-cost Machine-Type Communications (MTC) User Equipments (UEs) based on LTE, 3GPP, TR. 36.888, (Aug. 2013).Google Scholar
  13. 13.
    Baas, B. M. (1999). A low-power, high-performance, 1024-point FFT processor. IEEE Journal of Solid-State Circuits, 34(3), 380–387.CrossRefGoogle Scholar
  14. 14.
    3rd Generation Partnership Project, Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical channels and modulation, 3GPP TS 36.211 V8.0.0 (Sept. 2007).Google Scholar
  15. 15.
    3rd Generation Partnership Project, Evolved Universal Terrestrial Radio Access (E-UTRA); User Equipment (UE) Radio Transmission and Reception, 3GPP TS 36.101 V8.0.0 (Sept. 2007).Google Scholar
  16. 16.
    Duhamel, P., & Vetterli, M. (1990). Fast Fourier transforms: A tutorial review and a state of the art. Signal Processing, 19(4), 259–299.MathSciNetCrossRefGoogle Scholar
  17. 17.
    Yavne, R. (1968). An economical method for calculating the discrete Fourier transform. In Proc. AFIPS fall joint computer conf. (Vol. 33, pp. 115–125).Google Scholar
  18. 18.
    Van Berkel, C. H. (Apr. 2009). Multi-core for mobile phones. Design, automation & test in Europe conference & exhibition. DATE’09 (pp. 1260–1265).Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Xiaoming Dai
    • 1
    Email author
  • Zhenyu Zhang
    • 1
  • Linglong Dai
    • 2
  • Baoming Bai
    • 3
  1. 1.University of Science and Technology BeijingBeijingChina
  2. 2.Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Electronic EngineeringTsinghua UniversityBeijingChina
  3. 3.State Key Laboratory of ISNXidian UniversityXi’anChina

Personalised recommendations