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A DFT-based Low Complexity LMMSE Channel Estimation Technique for OFDM Systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The linear minimum mean square error (LMMSE) channel estimation technique is often employed in orthogonal frequency division multiplexing (OFDM) systems because of its optimal performance in the mean square error (MSE) performance. However, the LMMSE method requires cubic complexity of order O(N 3 p ), where Np is the number of pilot subcarriers. To reduce the computational complexity, a discrete Fourier transform (DFT) based LMMSE method is proposed in this paper for OFDM systems in the frequency selective channel. To validate the proposed method, the closed form mean square error (MSE) expression is also derived. Finally, a computer simulation is carried out to compare the performance of the proposed LMMSE method with the classical LS and LMMSE methods in terms of bit error rate (BER) and computational complexity. Results of the simulation show that the proposed LMMSE method achieves exactly the same performance as the conventional LMMSE method, with much lower computational complexity.
Słowa kluczowe
Rocznik
Tom
Strony
72--78
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India
  • Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India
autor
  • National Institute of Technology, Rourkela, Odisha, India
Bibliografia
  • [1] T. Hwang, C. Yang, G.Wu, S. Li, and G. Ye Li, „OFDM and its wireless applications: A survey", IEEE Trans. on Veh. Technol., vol. 58, no. 4, pp. 1673-1694, 2009 (DOI: 10.1109/TVT.2008.2004555).
  • [2] S. B. Y. Aimer, B. S. Bouazza, and C. Duvanaud, „Interleaving technique implementation to reduce PAPR of OFDM signal in presence of nonlinear amplification with memory effects", J. of Telecommun. and Inform. Technol., no. 3, pp. 14-22, 2018 (DOI: 10.26636/jtit.2018.123517).
  • [3] P. Vimala and G. Yamuna, „Pilot design for sparse channel estimation in orthogonal frequency division multiplexing systems", J. of Telecommun. and Inform. Technol., no. 2, pp. 60-68, 2018 (DOI: 10.26636/jtit.2018.113817).
  • [4] J.-J. Van De Beek, O. Edfors, M. Sandell, S. K. Wilson, and P. O. Borjesson, „On channel estimation in OFDM systems", in Proc. of IEEE 45th Veh. Technol. Conf. Count. to the Wirel. Twenty-First Cent., Chicago, IL, USA, 1995, pp. 815-819 (DOI: 10.1109/VETEC.1995.504981).
  • [5] M.-H. Hsieh and C.-H. Wei, „Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels", IEEE Trans. on Consumer Electron., vol. 44, no. 1, pp. 217-225, 1998 (DOI: 10.1109/30.663750).
  • [6] C. M. B. P. Sure, „A survey on OFDM channel estimation techniques based on denoising strategies", Int. J. of Engin. Sci. and Technol., vol. 20, no. 2, pp. 629-636, 2017 (DOI: 10.1016/j.jestch.2016.09.011).
  • [7] X. L. Xiao Zhou, Zhun Ye, and C. Wang, „Channel estimation based on linear filtering least square in OFDM systems", J. of Commun., vol. 11, no. 11, pp. 1005-1011, 2016 (DOI: 10.12720/jcm.11.11.1005-1011).
  • [8] P. K. Pradhan, O. Faust, S. K. Patra, and B. K. Chua, „Channel estimation algorithms for OFDM systems", Int. J. of Sig. and Imag. Syst. Engin., vol. 5, no. 4, pp. 267-273, 2012 (DOI: 10.1504/IJSISE.2012.050324).
  • [9] E. Hari Krishna, K. Sivani, and K. A. Reddy, „New channel estimation method using singular spectrum analysis for OFDM systems", Wirel. Pers. Commun., vol. 101, no. 4, p. 2193-2207, 2018 (DOI: 10.1007/s11277-018-5811-5).
  • [10] V. Vasylyshyn, „Channel estimation method for OFDM communication system using adaptive singular spectrum analysis", in Proc. IEEE 40th Int. Conf. on Electron. and Nanotechnol. ELNANO 2020, Kyiv, Ukraine, 2020, pp. 884-887 (DOI: 10.1109/ELNANO50318.2020.9088787).
  • [11] O. Edfors, M. Sandell, J.-J. Van de Beek, S. K. Wilson, and P. O. Borjesson, „OFDM channel estimation by singular value decomposition", IEEE Trans. on Commun., vol. 46, no. 7, pp. 931-939, 1998 (DOI: 10.1109/26.701321).
  • [12] V. Savaux, Y. Louet, and F. Bader, „Low-complexity approximations for LMMSE channel estimation in OFDM/OQAM", in Proc. 23rd Int. Conf. on Telecommun. ICT 2016 Thessaloniki, Greece, 2016 (DOI: 10.1109/ICT.2016.7500464).
  • [13] G. H. Golub and C. F. Van Loan, Matrix Computations, 3rd ed. The Johns Hopkins University Press, 1996 (ISBN: 9780801854149).
  • [14] S. Ohno, S. Munesada, and E. Manasseh, „Low-complexity approximate LMMSE channel estimation for OFDM systems", in Proc. Of the 2012 Asia-Paci_c Sign. and Inform. Process. Assoc. Ann. Summit and Conf. APSIPA 2012, Hollywood, CA, USA, 2012 [Online]. Available: https://ieeexplore.ieee.org/document/6411093
  • [15] N. Geng, X. Yuan, and L. Ping, „Dual-diagonal LMMSE channel estimation for OFDM systems", IEEE Trans. on Sig. Process., vol. 60, no. 9, pp. 4734-4746, 2012 (DOI: 10.1109/TSP.2012.2202112).
  • [16] L. Fang and D. Huang, „Neumann series expansion based LMMSE channel estimation for OFDM systems", IEEE Communications Letters, vol. 20, no. 4, pp. 748-751, 2016 (DOI: 10.1109/TSP.2012.2202112).
  • [17] R. Xin, Z. Ni, S. Wu, L. Kuang, and C. Jiang, „Low-complexity joint channel estimation and symbol detection for OFDMA systems", China Commun., vol. 16, no. 7, pp. 49-60, 2019 (DOI: 10.23919/JCC.2019.07.004).
  • [18] A. Khliff and R. Bouallegue, „An accurate and very low complexity LMMSE channel estimation technique for OFDM systems", Wirel. Pers. Commun., vol. 88, no. 4, pp. 911-922, 2016 (DOI:10.1007/s11277-016-3219-7).
  • [19] A. Zaib and S. Khattak, „Structure-based low complexity MMSE channel estimator for OFDM wireless systems", Wirel. Pers. Commun., vol. 97, no. 4, pp. 5657-5674, 2017 (DOI: 10.1007/s11277-017-4800-4).
  • [20] K. Kavitha and S. Manikandan, „LMMSE channel estimation algorithm based on channel autocorrelation minimization for LTEAdvanced with adaptive guard interval", Wirel. Pers. Commun., vol. 81, no. 3, pp. 1233-1241, 2015 (DOI: 10.1007/s11277-014-2181-5).
  • [21] A. Munshi and S. Unnikrishnan, „Performance analysis of compressive sensing based LS and MMSE channel estimation algorithm", J. of Commun. Softw. and Syst., vol. 17, no. 1, pp. 13-19, 2021 (DOI: 10.24138/jcomss.v17i1.1084).
  • [22] H. Wu, „LMMSE channel estimation in OFDM systems: A vector quantization approach", IEEE Commun. Lett., vol. 25, no. 6, pp. 1994-1998, 2021 (DOI: 10.1109/LCOMM.2021.3059776).
  • [23] Y.-J. Kim and G.-H. Im, „Pilot-symbol assisted power delay profile estimation for MIMO-OFDM systems", IEEE Commun. Lett., vol. 16, no. 1, pp. 68-71, 2012 (DOI: 10.1109/LCOMM.2011.110711.112047).
  • [24] S. Coleri, M. Ergen, A. Puri, and A. Bahai, „Channel estimation techniques based on pilot arrangement in OFDM systems", IEEE Trans. on Broadcast., vol. 48, no. 3, pp. 223-229, 2002 (DOI: 10.1109/TBC.2002.804034).
  • [25] R. M. Gray, Toeplitz and Circulant Matrices: A Review. Foundations and Trends in Communications and Information Theory. Now Publishers Inc, 2006 (ISBN-13: 9781933019239).
  • [26] Y. S. Cho, J. Kim, W. Y. Yang, and C. G. Kang, MIMO-OFDM Wireless Communications with MATLAB. Wiley, 2010 (DOI:10.1002/9780470825631, ISBN:9780470825617).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dbc8b0c7-9ed7-48bd-8ec3-d1cff7cbe07e
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