Abstract
In this paper, we propose two novel semi-blind channel estimation techniques based on QR decomposition for Rayleigh flat fading Multiple Input Multiple output (MIMO) channel using various pilot symbols. In the first technique, the flat-fading MIMO channel matrix H can be decomposed as an upper triangular matrix R and a unitary rotation matrix Q as H = RQ. The matrix R is estimated blindly from only received data by using orthogonal matrix triangularization based house holder QR decomposition, while the optimum rotation matrix Q is estimated exclusively from pilot based Orthogonal Pilot Maximum Likelihood Estimator (OPML) algorithm. In the second technique, joint semi-blind channel and data estimation is performed using QR decomposition based Least Square (LS) algorithm. Simulations have taken under 4-PSK data modulation scheme for two transmitters and six receiver antennas using various training symbols. Finally, these two new techniques compare with Whitening Rotation (WR) based semi-blind channel estimation technique and results shows that those new techniques achieve very nearby performance with low complexity compare to Whitening rotation based technique. Also first technique with perfect R outperforms Whitening Rotation based technique.
Highlights
A Multiple Input Multiple Output (MIMO) communication system uses multiple antennas at the transmitter and receiver to achieve numerous advantages
We propose two novel semi-blind channel estimation techniques based on QR decomposition for Rayleigh flat fading Multiple Input Multiple output (MIMO) channel using various pilot symbols
BER is evaluated for training based Least Square (LS) channel estimation technique, Whitening Rotation (WR) based semi-blind channel estimation technique, proposed matrix triangularization based Householder QR decomposition semi-blind channel estimation and proposed QR decomposition based joint semi-blind channel and data estimation technique in a Rayleigh flat fading MIMO channel
Summary
Whitening Rotation (WR) based semi blind technique with Orthogonal Pilot Maximum Likelihood (OPML) [14,15,16,17] has shown very good performance compare to other sub-optimal techniques and training based channel estimation techniques. Second proposed technique is based on joint semi-blind channel and data estimation. Step 3: Given data estimation and received Output, perform blind channel estimation using Same method. These two new proposed techniques shows near by performance compare to WR based techniques with low computational cost and first technique with perfect knowledge of R shows better result.
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More From: International Journal of Communications, Network and System Sciences
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