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Pilot Design for Sparse Channel Estimation in Orthogonal Frequency Division Multiplexing Systems

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique used in modern wide band wireless communication systems. Coherent OFDM systems achieve its advantages over a multipath fading channel, if channel impulse response is estimated precisely at the receiver. Pilot-aided channel estimation in wide band OFDM systems adopts the recently explored compressive sensing technique to decrease the transmission overhead of pilot subcarriers, since it exploits the inherent sparsity of the wireless fading channel. The accuracy of compressive sensing techniques in sparse channel estimation is based on the location of pilots among OFDM subcarriers. A sufficient condition for the optimal pilot selection from Sylow subgroups is derived. A Sylow subgroup does not exist for most practical OFDM systems. Therefore, a deterministic pilot search algorithm is described to select pilot locations based on minimizing coherence, along with minimum variance. Simulation results reveal the effectiveness of the proposed algorithm in terms of bit error rate, compared to the existing solutions.
Rocznik
Tom
Strony
60--68
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
autor
  • Department of Electronics and Communication Engineering, Annamalai University, Tamil Nadu, India
autor
  • Department of Electronics and Communication Engineering, Annamalai University, Tamil Nadu, India
Bibliografia
  • [1] Y. S. Cho, J. K. Won, Y. Y. Chung, and G. Kang, MIMO-OFDM Wireless Communication with MATLAB. Singapore: Wiley & Sons (Asia), 2010 (doi: 10.1002/9780470825631).
  • [2] Y. Li, “Pilot-symbol-aided channel estimation for OFDM in wireless systems”, IEEE Trans. on Vehicular Technol., vol. 49, no. 4, pp. 1207–1215, 2000 (doi: 10.1109/25.875230).
  • [3] M. H. Hsieh and Ch. 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).
  • [4] R. Negi and J. Cioffi, “Pilot tone selection for channel estimation in a mobile OFDM system”, IEEE Trans. on Consumer Electron., vol. 44, no. 3, pp. 1122–1128, 1998 (doi: 10.1109/30.713244).
  • [5] D. L. Donoho, “Compressed sensing”, IEEE Trans. on Inform. Theory, vol. 52, no. 4, pp. 1289–1306, 2006 (doi: 10.1109/TiT.2006.871582).
  • [6] W. U. Bajwa, “New information processing theory and methods for exploiting sparsity in wireless Systems”, Ph.D. Dissertation, University of Wisconsin, Madison, WI, USA, 2009.
  • [7] L. Applebaum et al., “Deterministic pilot sequences for sparse channel estimation in OFDM systems”, in Proc. of 17th Int. Conf. on Digit. Sig. Process. DSP 2011, Corfu, Greece, 2011, pp. 1–7 (doi: 10.1109/ICDSP.2011.6005021).
  • [8] Ch. Qi and L. Wu, “Optimized Pilot placement for sparse channel estimation in OFDM systems”, IEEE Sig. Process. Lett., vol. 18, no. 12, pp. 749–752, 2011 (doi: 10.1109/LSP.2011.2170834).
  • [9] Ch. R. Berger, J. Gomes, and J. M. F. Moura, “Study of pilot designs for cyclic-prefix OFDM on time-varying and sparse underwater acoustic channels”, in Proc. of IEEE Oceans Conf., Santander, Spain, 2011, pp. 1–8 (doi: 10.1109/Oceans-Spain.2011.6003627).
  • [10] Ch. Qi and L. Wu, “Tree-based backward pilot generation for sparse channel estimation”, Electron. Lett., vol. 48, no. 9, pp. 501–503, 2012 (doi: 10.1049/el.2012.0010).
  • [11] J. Ch. Chen, Ch. K. Wen, and P. Ting, “An efficient pilot design scheme for sparse channel estimation in OFDM systems”, IEEE Commun. Lett., vol. 17, no. 7, pp. 1352–1355, 2013 (doi: 10.1109.LCOMM.2013.051313.122933).
  • [12] P. Pakrooh, A. Amini, and F. Marvasti, “OFDM pilot allocation for sparse channel estimation”, EURASIP J. of Adv. Sig. Process., vol. 59, no. 1, pp. 1–9, 2012 (doi: 10.1186/1687-6180-2012-59).
  • [13] M. Khosravi and S. Mashhadi, “Joint pilot power pattern design for compressive OFDM channel estimation”, IEEE Commun. Lett., vol. 19, no. 1, pp. 50–53, 2013 (doi: 10.1109/LCOMM.2014.2371036).
  • [14] Ch. Qi et al., “Pilot design scheme for sparse channel estimation in OFDM systems”, IEEE Trans. on Vehicular Technol., vol. 64, no. 4, pp. 1493–1505, 2015 (doi: 10.1109/TVT.2014.2331085).
  • [15] S. Hadi, S. Masoumian, and B. M. Tazehkand, “Greedy deterministic pilot pattern algorithms for OFDM sparse channel estimation”, Wirel. Personal Commun., vol. 84, no. 2, pp. 1119–1132, 2015 (doi: 10.1007/s11277-015-2679-5).
  • [16] D. L. Donoho and X. Huo, “Uncertainty principles and ideal atomic decomposition”, IEEE Trans. on Inform. Theory, vol. 47, no. 7, pp. 2845–2862, 2001 (doi: 10.1109/18.959265).
  • [17] A. Ganesh, Z. Zhou, and Y. Ma, “Separation of a subspace signal: Algorithms and conditions”, in Proc. of IEEE Int. Con. on Acoust. Speech Sig. Process. ICASSP 2009, Taipei, Taiwan, 2009, pp. 3141–3144 (doi: 10.1109/ICASSP.2009.4960290).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ad5862d7-e741-4679-9ae5-a04b171378f2
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