access icon free Sparse inverse fast Fourier transform-based channel estimation for millimetre-wave vector orthogonal frequency division multiplexing systems

© The Institution of Engineering and Technology
Received 15/12/2016, Accepted 14/03/2017, Revised 28/02/2017, Published 27/04/2017

Millimetre-wave propagation is a promising broadband transmission technology for future fifth generation mobile communication systems. For a vector orthogonal frequency division multiplexing system, the authors investigate the millimetre-wave propagation through a sparse multipath channel in a sense that it has a large time delay spread but with only a few non-zero taps. By exploiting the sparse nature of millimetre-wave channel, any sparse multipath channel can be characterised by the multipath delays and their corresponding channel coefficients. They first study an ideal case that the pilot signals are transmitted through a sparse channel without noise, and an exactly sparse inverse fast Fourier transform (SIFFT) algorithm is performed to estimate the non-zero channel taps with reduced complexity. Then, they consider a more practical scenario that the pilot signals through a sparse channel with noise interference, and an approximately SIFFT algorithm is employed to estimate the effective channel taps, while the remaining small coefficients interfered by noise can be wiped out. Through numerical analysis, they demonstrate that the proposed SIFFT algorithms can reduce the computational complexity while keeping the root mean squared error of channel estimation at a low level.

Inspec keywords: OFDM modulation; wireless channels; 5G mobile communication; Fourier transforms; channel estimation

Other keywords: sparse inverse fast Fourier transform; millimetre-wave channel; non-zero channel taps; orthogonal frequency division multiplexing system; sparse multipath channel; non-zero taps; noise interference; sparse inverse fast Fourier transform algorithm; millimetre wave vector orthogonal frequency division multiplexing systems; channel coefficients; numerical analysis; fifth generation mobile communication systems; SIFFT algorithm; channel estimation; broadband transmission technology

Subjects: Communication channel equalisation and identification; Integral transforms in numerical analysis; Mobile radio systems; Modulation and coding methods

References

    1. 1)
      • 21. Kokshoorn, M., Chen, H., Wang, P., et al: ‘Millimeter wave MIMO channel estimation using overlapped beam patterns and rate adaptation’, IEEE Trans. Signal Process., 2017, 65, (3), pp. 601–616.
    2. 2)
      • 7. Pancaldi, F., Vitetta, G., Kalbasi, R., et al: ‘Single-carrier frequency-domain equalization’, IEEE Signal Process. Mag., 2008, 25, (5), pp. 37–56.
    3. 3)
      • 13. Han, C., Hashimoto, T., Suehiro, N.: ‘Constellation-rotated vector OFDM and its performance analysis over Rayleigh fading channels’, IEEE Trans. Commun., 2010, 58, (3), pp. 828–838.
    4. 4)
      • 5. Hwang, T., Yang, C., Wu, G., et al: ‘OFDM and its wireless applications: a survey’, IEEE Trans. Veh. Technol., 2009, 58, (4), pp. 1673–1694.
    5. 5)
      • 14. Han, C., Hashimoto, T.: ‘Tight PEP lower bound for constellation-rotated vector-OFDM under carrier frequency offset and fast fading’, IEEE Trans. Commun., 2014, 62, (6), pp. 1931–1943.
    6. 6)
      • 26. Hassanieh, H., Indyk, P., Katabi, D., et al: ‘Simple and practical algorithm for sparse Fourier transform’. Proc. 23rd Annual ACM-SIAM Symp. on Discrete Algorithms, Kyoto, Japan, January 2012, pp. 1183–1194.
    7. 7)
      • 27. Hassanieh, H., Indyk, P., Katabi, D., et al: ‘Nearly optimal sparse Fourier transform’. Proc. 44th Annual ACM Symp. on Theory of Computing, New York, NY, USA, May 2012, pp. 563–578.
    8. 8)
      • 15. Cheng, P., Tao, M., Xiao, Y., et al: ‘V-OFDM: on performance limits over multi-path Rayleigh fading channels’, IEEE Trans. Commun., 2011, 59, (7), pp. 1878–1892.
    9. 9)
      • 24. Berger, C.R., Zhou, S., Preisig, J.C., et al: ‘Sparse channel estimation for multicarrier underwater acoustic communication: from subspace methods to compressed sensing’, IEEE Trans. Signal Process., 2010, 58, (3), pp. 1708–1721.
    10. 10)
      • 6. Wang, N., Blostein, S.D.: ‘Comparison of CP-based single carrier and OFDM with power allocation’, IEEE Trans. Commun., 2005, 53, (3), pp. 391–394.
    11. 11)
      • 10. Li, Y., Ngebani, I., Xia, X.-G., et al: ‘On performance of vector OFDM with linear receivers’, IEEE Trans. Signal Process., 2012, 60, (10), pp. 5268–5280.
    12. 12)
      • 17. Ngebani, I., Li, Y., Xia, X.-G., et al: ‘Analysis and compensation of phase noise in vector OFDM systems’, IEEE Trans. Signal Process., 2014, 62, (23), pp. 6143–6157.
    13. 13)
      • 3. Cimini, L.J.: ‘Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing’, IEEE Trans. Commun., 1985, COM-33, (7), pp. 665–675.
    14. 14)
      • 28. Tropp, J.A., Gilbert, A.C.: ‘Signal recovery from random measurements via orthogonal matching pursuit’, IEEE Trans. Inf. Theory, 2007, 53, (12), pp. 4655–4666.
    15. 15)
      • 2. Roh, W., Seol, J.-Y., Park, J., et al: ‘Millimeter-wave beamforming as an enabling technology for 5G cellular communications: theoretical feasibility and prototype results’, IEEE Commun. Mag., 2014, 52, (2), pp. 106–113.
    16. 16)
      • 18. Ngebani, I., Li, Y., Xia, X.-G., et al: ‘EM-based phase noise estimation in vector OFDM systems using linear MMSE receivers’, IEEE Trans. Veh. Technol., 2016, 65, (1), pp. 110–122.
    17. 17)
      • 11. Zhang, H., Xia, X.-G., Cimini, L.J., et al: ‘Synchronization techniques and guard-band-configuration scheme for single-antenna vector-OFDM systems’, IEEE Trans. Wirel. Commun., 2005, 4, (5), pp. 2454–2464.
    18. 18)
      • 22. Lee, G., Sung, Y., Kountouris, M.: ‘On the performance of random beamforming in sparse millimeter wave channels’, IEEE J. Sel. Top. Signal Process., 2016, 10, (3), pp. 560–575.
    19. 19)
      • 12. Zhang, H., Xia, X.-G.: ‘Iterative decoding and demodulation for single-antenna vector OFDM systems’, IEEE Trans. Veh. Technol., 2006, 55, (4), pp. 1447–1454.
    20. 20)
      • 9. Xia, X.-G.: ‘Precoded and vector OFDM robust to channel spectral nulls and with reduced cyclic prefix length in single transmit antenna systems’, IEEE Trans. Commun., 2001, 49, (8), pp. 1363–1374.
    21. 21)
      • 8. Falconer, D., Ariyavisitakul, S.L., Benyamin-Seeyar, A., et al: ‘Frequency domain equalization for single-carrier broadband wireless systems’, IEEE Commun. Mag., 2002, 40, (4), pp. 58–66.
    22. 22)
      • 1. Salous, S., Degli Esposti, V., Fuschini, F., et al: ‘Millimeter-wave propagation’, IEEE Antennas Propag. Mag., 2016, 58, (6), pp. 115–127.
    23. 23)
      • 20. Rappaport, T.S., MacCartney, G.R., Samimi, M.K., et al: ‘Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design’, IEEE Trans. Commun., 2015, 63, (9), pp. 3029–3056.
    24. 24)
      • 25. Schreiber, W.F.: ‘Advanced television systems for terrestrial broadcasting: some problems and some proposed solutions’, Proc. IEEE, 1995, 83, (6), pp. 958–981.
    25. 25)
      • 4. Astély, D., Dahlman, E., Furuskär, , et al: ‘LTE: the evolution of mobile broadband’, IEEE Commun. Mag., 2009, 47, (4), pp. 44–51.
    26. 26)
      • 19. Akdeniz, M.R., Liu, Y., Samimi, M.K., et al: ‘Millimeter wave channel modeling and cellular capacity evaluation’, IEEE J. Sel. Areas Commun., 2014, 32, (6), pp. 1164–1179.
    27. 27)
      • 23. Win, M.Z., Scholtz, R.A.: ‘Characterization of an ultra-wideband wireless indoor channel: a communication-theoretic view’, IEEE J. Sel. Areas Commun., 2002, 20, (9), pp. 1613–1627.
    28. 28)
      • 16. Zhou, W., Fan, L., Chen, H.: ‘Vector orthogonal frequency division multiplexing system over fast fading channels’, IET Commun., 2014, 8, (13), pp. 2322–2335.
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