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DRM Channel Estimation via OMP Algorithm

Yang Nie
Vol. 1, No. 1, pp. 1-4, 2024 DOI: 10.54097/meca7h17 November 26, 2024
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Abstract.Digital Radio Mondiale (DRM) standard is the most mature digital broadcasting system standard all over the world. Due to the limited spectrum characteristics of DRM communication systems, pilot-based DRM channel estimation brings great challenges. In this paper, the channel estimation problem is transformed into a sparse recovery problem by leveraging the compressed sensing problem. Subsequently, the orthogonal matching pursuit (OMP) sparse recovery algorithm is employed to obtain accurate estimation performance with a lower pilot overhead. Compared with the traditional least square algorithm, simulation results demonstrate that the OMP-based channel estimation algorithm can obtain accurate estimation results with lower pilots, and improve the spectrum utilization while improving the estimation performance.
Keywords. Channel Estimation OMP Algorithm Pilot Design Compressed Sensing
APA Citation Yang Nie (2024). DRM Channel Estimation via OMP Algorithm. Journal of Computer Science and Artificial Intelligence, 1(1), 1-4. https://doi.org/10.54097/meca7h17

References

  1. Donoho D L. Compressed sensing [J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
  2. Baraniuk R G. Compressive sensing [J]. IEEE Signal Processing Magazine, 2007, 24(4): 118-121.
  3. Candès E J, Wakin M B. An introduction to compressive sampling [J]. IEEE Signal Processing Magazine, 2008, 25(2): 21-30.
  4. Tong L, Zhao Q. Joint order detection and blind channel estimation by least squares smoothing [J]. IEEE Transactions on Signal Processing, 1999, 47(9): 2345-2355.
  5. Coleri S, Ergen M, Puri A, et al. Channel estimation techniques based on pilot arrangement in OFDM systems [J]. IEEE Transactions on broadcasting, 2002, 48(3): 223-229.
  6. Hsieh M H, Wei C H. Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels [J]. IEEE Transactions on Consumer Electronics, 1998, 44(1): 217-225.
  7. Cotter S F, Rao B D. Sparse channel estimation via matching pursuit with application to equalization [J]. IEEE Transactions on Communications, 2002, 50(3): 374-377.
  8. Bajwa W U, Haupt J, Sayeed A M, et al. Compressed channel sensing: A new approach to estimating sparse multipath channels [J]. Proceedings of the IEEE, 2010, 98(6): 1058-1076.