Performance Improvement in Estimation of Spatially Correlated Rician Fading MIMO Channels Using a New LMMSE Estimator

DOI: 10.4236/ijcns.2010.312131   PDF   HTML     7,480 Downloads   10,800 Views   Citations


In most of the previous researches on the multiple-input multiple-output (MIMO) channel estimation, the fading model has been assumed to be Rayleigh distributed. However, the Rician fading model is suitable for microcellular mobile systems or line of sight mode of WiMAX. In this paper, the training based channel es-timation (TBCE) scheme in the spatially correlated Rician flat fading MIMO channels is investigated. First, the least squares (LS) channel estimator is probed. Simulation results show that the Rice factor has no effect on the performance of this estimator. Then, a new linear minimum mean square error (LMMSE) technique, appropriate for Rician fading channels, is proposed. The optimal choice of training sequences with mean square error (MSE) criteria is investigated for these estimators. Analytical and numerical results show that the performance of proposed estimator in the Rician channel model compared with Rayleigh one is much better. It is illustrated that when the channel Rice factor and/or the correlation coefficient increase, the per-formance of the proposed estimator significantly improves.

Share and Cite:

H. Nooralizadeh and S. Moghaddam, "Performance Improvement in Estimation of Spatially Correlated Rician Fading MIMO Channels Using a New LMMSE Estimator," International Journal of Communications, Network and System Sciences, Vol. 3 No. 12, 2010, pp. 962-971. doi: 10.4236/ijcns.2010.312131.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] D. Tse and P. Viswanath, “Fundamentals of Wireless Communication,” Cambridge University Press, Cambridge, 2005.
[2] I. E. Telatar, “Capacity of Multi-Antenna Gaussian Channels,” European Transactions on Telecommunications, Vol. 10, No. 6, November 1999, pp. 585-595.
[3] S. K. Jayaweera and H. V. Poor, “On the Capacity of Multiple-Antenna Systems in Rician Fading,” IEEE Transactions on Wireless Communications, Vol. 4, No. 3, May 2005, pp. 1102-1111.
[4] M. Biguesh and A. B. Gershman, “Training-Based MIMO Channel Estimation: A Study of Estimator Tradeoffs and Optimal Training Signals,” IEEE Transactions on Signal Processing, Vol. 54, No. 3, March 2006, pp. 884-893.
[5] X. Ma, L. Yang and G. B. Giannakis, “Optimal Training for MIMO Frequency-Selective Fading Channels,” IEEE Transactions on Wireless Communications, Vol. 4, No. 2, March 2005, pp. 453-466.
[6] G. Leus and A.-J. von der Veen, “Optimal Training for ML and LMMSE Channel Estimation in MIMO Systems,” Proceedings of 13th IEEE Workshop on Statistical Signal Processing, Bordeaux, 17-20 July 2005, pp. 1354-1357.
[7] H. Vikalo, B. Hassibi, B. Hochwald and T. Kailath, “On the Capacity of Frequency-Selective Channels in Training-Based Transmission Schemes,” IEEE Transactions on Signal Processing, Vol. 52, No. 9, September 2004, pp. 2572-2583.
[8] S. A. Yang and J. Wu, “Optimal Binary Training Sequence Design for Multiple-Antenna Systems over Dispersive Fading Channels,” IEEE Transactions on Vehicular Technology, Vol. 51, No. 5, September 2002, pp. 1271-1276.
[9] W. Yuan, P. Wang and P. Fan, “Performance of Multi- Path MIMO Channel Estimation Based on ZCZ Training Sequences,” Proceedings of IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, Vol. 2, Beijing, 8-12 August 2005, pp. 1542-1545.
[10] S. Wang and A. Abdi, “Aperiodic Complementary Sets of Sequences-Based MIMO Frequency Selective Channel Estimation,” IEEE Communication Letters, Vol. 9, No. 10, October 2005, pp. 891-893.
[11] S. Wang and A. Abdi, “Low-Complexity Optimal Estimation of MIMO ISI Channels with Binary Training Sequences,” IEEE Signal Processing Letters, Vol. 13, No. 11, November 2006, pp. 657-660.
[12] S. Wang and A. Abdi, “MIMO ISI Channel Estimation Using Uncorrelated Golay Complementary Sets of Poly- Phase Sequences,” IEEE Transactions on Vehicular Technology, Vol. 56, No. 5, September 2007, pp. 3024-3039.
[13] H. M. Wang, X. Q. Gao, B. Jiang, X. H. You and W. Hong, “Efficient MIMO Channel Estimation Using Complementary Sequences,” IET Communications, Vol. 1, No. 5, October 2007, pp. 962-969.
[14] W. Dong, J. Li and Z. Lu, “Parameter Estimation for Correlated MIMO Channels with Frequency-Selective Fading,” Wireless Personal Communications, Vol. 52, No. 4, March 2010, pp. 813-828.
[15] J. Pang, J. Li, L. Zhao and Z. Lu, “Optimal Training Sequences for MIMO Channel Estimation with Spatial Correlation,” Proceedings of 66th IEEE Vehicular Technology Conference, Baltimore, 30 September-3 October 2007, pp. 651-655.
[16] J. Pang, J. Li, L. Zhao and Z. Lu, “Optimal Training Sequences for Frequency-Selective MIMO Correlated Fading Channels,” Proceedings of 21st IEEE International Conference on Advanced Information Networking and Applications, Niagara Falls, 21-23 May 2007, pp. 820- 824.
[17] M. Kiessling, J. Speidel and Y. Chen, “MIMO Channel Estimation in Correlated Fading Environments,” Proceedings of 58th IEEE Vehicular Technology Conference, Orlando, Vol. 2, 6-9 October 2003, pp. 1187-1191.
[18] G. Xie, X. Fang, A. Yang and Y. Liu, “Channel Estimation with Pilot Symbol and Spatial Correlation Information,” Proceedings of IEEE International Symposium on Communications and Information Technologies, Sydney, 16-19 October 2007, pp. 1003-1006.
[19] E. Bj?rnson and B. Ottersten, “Training-Based Bayesian MIMO Channel and Channel Norm Estimation,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, Taipei, 19-24 April 2009, pp. 2701-2704.
[20] D. Shiu, G. J. Foschini, M. J. Gans and J. M. Kahn, “Fading Correlation and Its Effect on the Capacity of Multi-Element Antenna Systems,” IEEE Transactions on Communications, Vol. 48, No. 3, March 2000, pp. 502- 513.
[21] H. Nooralizadeh and S. S. Moghaddam, “A Novel Shifted Type of SLS Estimator for Estimation of Rician Flat Fading MIMO Channels,” Signal Processing, Vol. 90, No. 6, June 2010, pp. 1887-1894.
[22] L. Huang, G. Mathew and J. W. M. Bergmans, “Pilot-Aided Channel Estimation for Systems with Virtual Carriers,” Proceedings of IEEE International Conference on Communications, Istanbul, 11-15 June 2006, pp. 3070-3075.
[23] S. M. Kay, “Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory,” Prentice-Hall, Upper Saddle River, 1993.
[24] K. Werner and M. Jansson, “Estimating MIMO Channel Covariances from Training Data under the Kronecker Model,” Signal Processing, Vol. 89, No. 1, January 2009, pp. 1-13.
[25] C. Mehlführer and M. Rupp, “Novel Tap-Wise LMMSE Channel Estimation for MIMO W-CDMA,” Proceedings of IEEE Global Telecommunications Conference, New Orleans, 30 November-4 December 2008, pp. 1-5.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.