Performance Enhancement of CPMIMO-OFDM System using Blind Channel Estimation

This paper deals with the blind channel estimation in CP MIMO-OFDM system based on subspace algorithm with reduced time samples to get time invariant system, eliminating the pilot based channel estimation and utilizing the bandwidth. This paper uses the statistical blind estimation technique by using second order statistic and in this the estimates can be obtained in a simple form by optimizing a quadratic cost function. These algorithms use the orthogonality of the noise and signal subspaces of the correlation matrix of the received signals to estimate the unknown channel coefficients. Simulation results show that the proposed approach improving the performance, observed by the graphs SER/SNR and MSE/SNR.

[1]  Yonghong Zeng,et al.  Robust subspace blind channel estimation for cyclic prefixed MIMO ODFM systems: algorithm, identifiability and performance analysis , 2008, IEEE Journal on Selected Areas in Communications.

[2]  Robert W. Heath,et al.  Blind Channel Estimation for MIMO-OFDM Systems , 2007, IEEE Transactions on Vehicular Technology.

[3]  Yonghong Zeng,et al.  A semi-blind channel estimation method for multiuser multiantenna OFDM systems , 2004, IEEE Transactions on Signal Processing.

[4]  Elisabeth de Carvalho,et al.  Blind and semi-blind FIR multichannel estimation: (global) identifiability conditions , 2004, IEEE Transactions on Signal Processing.

[5]  L. Tong,et al.  Multichannel blind identification: from subspace to maximum likelihood methods , 1998, Proc. IEEE.

[6]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[7]  Philippe Loubaton,et al.  A subspace algorithm for certain blind identification problems , 1997, IEEE Trans. Inf. Theory.

[8]  Georgios B. Giannakis,et al.  Direct blind equalizers of multiple FIR channels: a deterministic approach , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[9]  J. Cadzow Blind deconvolution via cumulant extrema , 1996, IEEE Signal Process. Mag..

[10]  T. Kailath,et al.  A least-squares approach to blind channel identification , 1995, IEEE Trans. Signal Process..

[11]  Eric Moulines,et al.  Subspace methods for the blind identification of multichannel FIR filters , 1995, IEEE Trans. Signal Process..

[12]  Lang Tong,et al.  Blind channel identification based on second-order statistics: a frequency-domain approach , 1995, IEEE Trans. Inf. Theory.

[13]  Lang Tong,et al.  Blind identification and equalization based on second-order statistics: a time domain approach , 1994, IEEE Trans. Inf. Theory.

[14]  Y. Li,et al.  Blind channel identification based on second order cyclostationary statistics , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[15]  Lang Tong,et al.  A new approach to blind identification and equalization of multipath channels , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[16]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .