This paper investigates the subspace channel identification for multiple-input multiple-output zero-padded orthogonal frequency-division multiplexing systems with space–time block code and virtual carriers (VCs). We first develop a new subspace channel identification model when the VCs exist. Then, two schemes, the forward–backward method and the repetition index scheme (RIS), are developed to generate many times equivalent symbols and then to enhance the performance of the subspace channel identification. With these methods, more accurate subspace channel identification can be obtained by using only a few received blocks. Further, the noise pre-whitening technique is investigated to decrease the nonwhite noise effect caused by the RIS scheme. We also provide complexity analyses of the proposed methods. With the acceptable computational cost, the proposed methods significantly improve the performances of the channel identification and the equalization. Simulations are carried out to demonstrate the effectiveness of the proposed methods.
This is a preview of subscription content, log in to check access.
This work was supported in part by the Special Foundation for Young Scientists of Quanzhou Normal University of China under Grant No. 201330, in part by Fujian Province Education Department under Grants JAT170470, in part by the National Natural Science Foundation of China under Grant 61501041, in part by the Open Foundation of State Key Laboratory under Grant ISN19-19, in part by the Ministry of Science and Technology, Taiwan under Grants MOST 107-2221-E-030-003 and in part by Fu-Jen Catholic University of Taiwan under Grant A0106014.
S.M. Alamouti, A simple transmit diversity technique for wireless communications. IEEE J. Sel. Areas Commun. 16(8), 1451–1458 (1998)CrossRefGoogle Scholar
E. Dahlman, S. Parkvall, J. Sköld, 4G LTE/LTE-Advanced for Mobile Broadband (Academic Press, London, 2011)Google Scholar
K. Fazal, S. Kaiser, Multi-carrier and Spread Spectrum Systems: from OFDM and MC-CDMA to LTE and WiMAX (Wiley, New York, 2008)CrossRefGoogle Scholar
F. Gao, Y. Zeng, A. Nallanathan, T.S. Ng, Robust subspace blind channel estimation for cyclic prefixed MIMO ODFM systems: algorithm, identifiability and performance analysis. IEEE J. Sel. Areas Commun. 26(2), 378–388 (2008)CrossRefGoogle Scholar
Q. Li, G. Li, W. Lee, M. Lee, D. Mazzarese, B. Clerckx, Z. Li, MIMO techniques in WiMAX and LTE: a feature overview. IEEE Commun. Mag. 48(5), 86–92 (2010)CrossRefGoogle Scholar
L. Luo, J. Zhang, L. Davis, Space-time block code and spatial multiplexing design for quadrature-OFDMA systems. IEEE Trans. Commun. 60(10), 3133–3142 (2012)CrossRefGoogle Scholar
Y.C. Pan, S.M. Phoong, An improved subspace-based algorithm for blind channel identification using few received blocks. IEEE Trans. Commun. 61(9), 3710–3720 (2013)CrossRefGoogle Scholar
A. Saci, A. Al-Dweik, A. Shami, Y. Iraqi, One-shot blind channel estimation for OFDM systems over frequency-selective fading channels. IEEE Trans. Commun. 65(12), 5445–5458 (2017)CrossRefGoogle Scholar
N. Sarmadi, S. Shahbazpanahi, A.B. Gershman, Blind channel estimation in orthogonally coded MIMO-OFDM systems: a semidefinite relaxation approach. IEEE Trans. Signal Process. 57(6), 2354–2364 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
B. Su, P.P. Vaidyanathan, A generalized algorithm for blind channel identification with linear redundant precoders. EURASIP J. Adv. Signal Process. 2007(1), 25672 (2007)MathSciNetCrossRefGoogle Scholar
G.L. Stüber, J.R. Barry, S.W. McLaughlin, Y. Li, M.A. Ingram, T.G. Pratt, Broadband MIMO-OFDM wireless communications. Proc. IEEE 92(2), 271–294 (2004)CrossRefGoogle Scholar
O. Tirkkonen, A. Hottinen, Square-matrix embeddable space-time block codes for complex signal constellations. IEEE Trans. Inform. Theory. 48(2), 384–395 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
C.C. Tu, B. Champagne, Subspace-based blind channel estimation for MIMO-OFDM systems with reduced time averaging. IEEE Trans. Veh. Technol. 59(3), 1539–1544 (2010)CrossRefGoogle Scholar
M. Wen, X. Cheng, M. Ma, B. Jiao, H.V. Poor, On the achievable rate of OFDM with index modulation. IEEE Trans. Signal Process. 64(8), 1919–1932 (2016)MathSciNetCrossRefGoogle Scholar
J.L. Yu, A low-complexity two-stage receivers for space–time block coded CDMA MIMO systems. Signal Process. 87(7), 1626–1641 (2007)CrossRefzbMATHGoogle Scholar
J.L. Yu, Y.C. Lin, Space–time-coded MIMO ZP-OFDM systems: semiblind channel estimation and equalization. IEEE Trans. Circuits Syst. I Regul. Pap. 56(7), 1360–1372 (2009)MathSciNetCrossRefGoogle Scholar
Y. Zeng, W.H. Lam, T.S. Ng, Semiblind channel estimation and equalization for MIMO space–time coded OFDM. IEEE Trans. Circuits Syst. I Regul. Pap. 53(2), 463–474 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
B. Zhang, J.L. Yu, Y. Yuan, J.W. Lai, Fast blind channel estimation for space-time block coded MIMO-OFDM systems. Telecommun. Syst. 65(3), 443–457 (2017)CrossRefGoogle Scholar
B. Zhang, J.L. Yu, Y. Yuan, C.Y. Wu, Convergence-enhanced subspace channel estimation for MIMO-OFDM systems with virtual carriers. Circuits Syst. Signal Process. 36(6), 2384–2401 (2017)MathSciNetCrossRefzbMATHGoogle Scholar
H. Zhang, D. Yuan, H.H. Chen, J.A. Nossek, Effects of channel estimation error on array processing based QO-STBC coded OFDM systems. IEEE Commun. Lett. 13(4), 212–214 (2009)CrossRefGoogle Scholar