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Circuits, Systems, and Signal Processing

, Volume 37, Issue 5, pp 2194–2205 | Cite as

FPGA Implementation of OFDM-Based mmWave Indoor Sparse Channel Estimation Using OMP

  • Praveen K. Korrai
  • K. Deergha Rao
  • Ch. Gangadhar
Short Paper
  • 141 Downloads

Abstract

Due to the sparse multipath characteristic of the channel, millimeter wave (mmWave) channel estimation can be treated as a sparse signal recovery problem. By exploiting the channel sparse characteristics with compressive sensing (CS) theory, sparse signal recovery algorithms can be used for channel estimation. Orthogonal matching pursuit (OMP) algorithm is one of the most popular CS reconstruction algorithms. Hence, in this paper, we present OFDM-based mmWave sparse indoor channel estimation using the OMP algorithm. However, the computational effort for OMP remains high, even for problems of moderate size in real-time applications. Hence, a new VLSI architecture for mmWave channel estimation using the OMP algorithm is designed and simulated using Xilinx 15.4 Vivado HLS simulator in this paper. Our empirical results illustrate the efficacy of the proposed approach.

Keywords

mmWave Channel estimation Compressive sensing FPGA VLSI architecture OMP 

References

  1. 1.
    A. Alkhateeb, O. El Ayach, G. Leus, R.W. Heath, Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE J. Sel. Top. Signal Process. 8(5), 831–846 (2014)CrossRefGoogle Scholar
  2. 2.
    L. Bai, P. Maechler, M. Muehlberghuber and H. Kaeslin, High-speed compressed sensing reconstruction on FPGA using OMP and AMP, in 2012 19th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Seville, pp. 53–56, 2012Google Scholar
  3. 3.
    T.R. Braun, An evaluation of GPU acceleration for sparse reconstruction. Proc. SPIE Signal Process. Sensor Fusion Target Recognit. XIX 7697, 769715-1–769715-10 (2010)Google Scholar
  4. 4.
    E. Candes, J. Romberg, T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inf. Theory 52(2), 489–509 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    D.L. Donoho, Compressed sensing. IEEE Trans. Inf. Theory 52(4), 12891306 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    P. Feng, Y. Bresler, Spectrum-blind minimum-rate sampling and reconstruction of multiband signals. Proc. IEEE Int. Conf. Accoustics. Speech Signal Process. (ICASSP) 3, 1688–1691 (1996)Google Scholar
  7. 7.
    A. Korde, D. Bradley, T. Mohsenin, Detection performance of radar compressive sensing in noisyenvironments, in International SPIE Conference on Defense, Security, and Sensing, May 2013Google Scholar
  8. 8.
    A. Maltsev, et al., Channel models for 60 GHz WLAN systems. IEEE Document 802.11-09/0334r8, May 2010Google Scholar
  9. 9.
    P. Maechler, P. Greisen, N. Felber, A. Burg, Matching pursuit: Evaluation and implementatio for LTE channel estimation, in Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS), Paris, pp. 589–592, 2010Google Scholar
  10. 10.
    M. Patrick, VLSI architectures for compressive sensing and sparse signal recovery, e-thesis, ETH Zurich, 2012Google Scholar
  11. 11.
    H. Rabah, A. Amira, B.K. Mohanty, S. Almaadeed, P.K. Meher, FPGA implementation of orthogonal matching pursuit for compressive sensing reconstruction. IEEE Trans. Very Large Scale Integr. Syst. 23(10), 2209–2220 (2015)CrossRefGoogle Scholar
  12. 12.
    T.S. Rappaport, Shu Sun, R. Mayzus, Hang Zhao, Y. Azar, K. Wang, G.N. Wong, J.K. Schulz, M. Samimi, F. Gutierrez, “Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!,” in Access, IEEE vol.1, 335–349 (2013)Google Scholar
  13. 13.
    Xilinx LogiCore IP Complex Multiplier v3.1Google Scholar
  14. 14.
    P. Zhouyue, F. Khan, An introduction to millimeter-wave mobile broadband systems. IEEE Commun. Mag. 49(6), 101–107 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.G S Sanyal School of TelecommunicationsIndian Institute of Technology KharagpurKharagpurIndia
  2. 2.Department of ECE, VCEOsmania UniversityHyderabadIndia
  3. 3.Department of ECEPVP Siddhartha Institute of TechnologyVijayawadaIndia

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