Stable adaptive sparse filtering algorithms for estimating multiple-input-multiple-output channels

IET Communications

Volumn 8, Issue 7, 2014, Pages 1032-1040

  Gui, Guan ^a   Adachi, Fumiyuki ^a  

^a TOHOKU UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CHANNEL ESTIMATION; COMPUTER SIMULATION; ESTIMATION; TELECOMMUNICATION REPEATERS;

ADAPTIVE CHANNEL ESTIMATION; ALGORITHM STABILITY; CONVENTIONAL METHODS; ESTIMATION PERFORMANCE; LEAST MEAN SQUARE ALGORITHMS; LOW SIGNAL-TO-NOISE RATIO; MULTIPLE-INPUT MULTIPLE-OUTPUT CHANNELS; SPARSE CHANNEL ESTIMATIONS;

SIGNAL TO NOISE RATIO;

EID: 84899635227     PISSN: 17518628     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-com.2013.0665     Document Type: Article

References (35)

1. Raychaudhuri, D., Mandayam, N.B.: 'Frontiers of wireless and mobile communications', Proc. IEEE, 2012, 100, (4), pp. 824-840
2. Adachi, F., Kudoh, E.: 'New direction of broadband wireless technology', Wirel. Commun. Mob. Comput., 2007, 7, (8), pp. 969-983
3. Dai, L.,Wang, Z., Yang, Z.: 'Spectrally efficient time-frequency training OFDM for mobile large-scale MIMO systems', IEEE J. Sel. Areas Commun., 2013, 31, (2), pp. 251-263
4. Sayeed, A.M.: 'Deconstructing multiantenna fading channels', IEEE Trans. Signal Process., 2002, 50, (10), pp. 2563-2579
5. Persson, D.B., Lau, K., Lau, B.K., et al.: 'Scaling up MIMO: Opportunities and challenges with very large arrays', IEEE Signal Process. Mag., 2013, 30, (1), pp. 40-60
6. Gibson, J.D., Iltis, R.A.: 'Channel estimation and data detection for MIMO-OFDM systems'. IEEE Global Telecommunications Conf. (GLOBECOM), San Francisco, USA, December 2003, pp. 581-585
7. Biguesh, M., Gershman, B.: 'Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals', IEEE Trans. Signal Process., 2006, 54, (3), pp. 884-893
8. Chang, T., Chiang,W., Hong, Y.P., et al.: 'Training sequence design for discriminatory channel estimation in wireless MIMO systems', IEEE Trans. Signal Process., 2010, 58, (12), pp. 6223-6237
9. He, S., Tugnait, J.K., Meng, X.: 'On superimposed training for MIMO channel estimation and symbol detection', IEEE Trans. Signal Process., 2007, 55, (6), pp. 3007-3021
10. Pham, T.-H., Liang, Y., Nallanathan, A.: 'A joint channel estimation and data detection receiver for multiuser MIMO IFDMA systems', IEEE Trans. Commun., 2009, 57, (6), pp. 1857-1865
11. Wang, Z.J., Han, Z., Liu, K.J.R.: 'A MIMO-OFDM channel estimation approach using time of arrivals', IEEE Trans. Wirel. Commun., 2005, 4, (3), pp. 1207-1213
12. Taubock, G., Hlawatsch, F., Eiwen, D., et al.: 'Compressive estimation of doubly selective channels in multicarrier systems: Leakage effects and sparsity-enhancing processing', IEEE J. Sel. Top. Signal Process., 2010, 4, (2), pp. 255-271
13. Bajwa, W.U., Haupt, J., Sayeed, A.M., et al.: 'Compressed channel sensing: a new approach to estimating sparse multipath channels', Proc. IEEE, 2010, 98, (6), pp. 1058-1076
14. Wang, N., Gui, G., Zhang, Z., et al.: 'A novel sparse channel estimation method for multipath MIMO-OFDM systems'. IEEE 74th Vehicular Technology Conf. (VTC-Fall), San Francisco, California, USA, September 2011, pp. 1-5
15. Lee, S.J.: 'On the training of MIMO-OFDM channels with least square channel estimation and linear interpolation', IEEE Commun. Lett., 2008, 12, (2), pp. 100-102
16. Gui, G., Peng, W., Adachi, F.: 'Sub-Nyquist rate ADC sampling-based compressive channel estimation', Wirel. Commun. Mob. Comput., 2013, article first publihed online, doi.10.1002/wcm2372
17. Zhou, Y., Sayeed, A.M.: 'Experimental study of MIMO channel statistics and capacity via virtual channel representation'. UW Tech. Report, http//www.dune.ece.wisc.edu/pdfs/zhoumeas.pdf
18. Czink, N., Yin, X., Özcelik, H., et al.: 'Cluster characteristics in a MIMO indoor propagation environment', IEEE Trans. Wirel. Commun., 2007, 6, (4), pp. 1465-1475
19. Vuokko, L., Kolmonen, V.-M., Salo, J., et al.: 'Measurement of large-scale cluster power characteristics for Geometric channel models', IEEE Trans. Antennas Propag., 2007, 55, (11), pp. 3361-3365
20. Candes, E.J., Romberg, J., Tao, T.: 'Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information', IEEE Trans. Inf. Theory, 2006, 2, (2), pp. 489-509
21. Donoho, D.L.: 'Compressed sensing', IEEE Trans. Inf. Theory, 2006, 52, (4), pp. 1289-1306
22. Dai, L., Wang, Z., Yang, Z.: 'Compressive sensing based time domain synchronous OFDM transmission for vehicular communications', IEEE J. Sel. Areas Commun., 2013, 31, (9), pp. 460-469
23. Candes, E.J.: 'The restricted isometry property and its implications for compressed sensing', Comptes Rendus Math., 2008, 1, (346), pp. 589-592
24. Amini, A., Unser, M., Marvasti, F.: 'Compressibility of deterministic and random infinite sequences', IEEE Trans. Signal Process., 2011, 59, (99), pp. 5193-5201
25. Taheri, O., Vorobyov, S.A.: 'Sparse channel estimation with Lp-norm and reweigthted L1-norm penalized least mean square'. IEEE Int. Conf. on Acoustics Speech and Signal Processing (ICASSP), Prague, Czech Republic, May 2011, pp. 2864-2867
26. Widrow, B., Stearns, D.: 'Adaptive signal processing' (Prentice-Hall, New Jersey, 1985)
27. Eweda, E.: 'Global stabilization of the least mean fourth algorithm', IEEE Trans. Signal Process., 2012, 60, (3), pp. 1473-1477
28. Gui, G., Adachi, F.: 'Adaptive sparse system identification using normalized least-mean fourth algorithm', Int. J. Commun. Syst., 2013, article first published online, doi: 10.1002/dac.2637
29. Gui, G., Peng, W., Adachi, F.: 'Improved adaptive sparse channel estimation based on the least mean square algorithm'. IEEE Wireless Communications and Networking Conf. (WCNC), Shanghai, China, April 2013, pp. 3130-3134
30. Gu, Y., Jin, J., Mei, S.: 'L0-norm constraint LMS algorithm for sparse system identification', IEEE Signal Process. Lett., 2009, 16, (9), pp. 774-777
31. Walach, E., Widrow, B.: 'The least mean fourth (LMF) adaptive algorithm and its family', IEEE Trans. Inf. Theory, 1984, 30, (2), pp. 275-283
32. Gui, G., Adachi, F.: 'Sparse LMF algorithm for adaptive channel estimation in low SNR region', Int. J. Commun. Syst., 2013, article first published online, doi: 10.1002/dac.2531
33. Olabiyi, O., Annamalai, A.: 'Invertible exponential-type approximations for the Gaussian probability integral', IEEE Wirel. Commun. Lett., 2012, 1, (5), pp. 544-547
34. Eweda, E., Bershad, N.J.: 'Stochastic analysis of a stable normalized least mean fourth algorithm for adaptive noise canceling with a white Gaussian reference', IEEE Trans. Signal Process., 2012, 60, (12), pp. 6235-6244
35. Hübscher, P.I., Bermudez, J.C.M., Nascimento, V.H.: 'A mean-square stability analysis of the least mean fourth adaptive algorithm', IEEE Trans. Signal Process., 2007, 55, (8), pp. 4018-4028