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Connections between the least-squares and the subspace approaches to blind channel estimation

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2 Author(s)
Zeng, H.H. ; Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA ; Lang Tong

In this correspondence, we study the connections between the least-squares and the subspace approaches to blind channel estimation. By examining the properties and connections of the so-called multichannel filtering and data selection transforms, we establish a relationship between the identification equations used in the two approaches. Next, it is shown that the least-squares and subspace estimators are identical for the case when there are two subchannels. In general, the two algorithms are different in their utilization of the noise subspace

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Signal Processing, IEEE Transactions on  (Volume:44 ,  Issue: 6 )