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Proceedings Paper

Adaptive blind channel estimation by least-squares smoothing for CDMA
Author(s): Qing Zhao; Lang Tong
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Paper Abstract

A least square smoothing (LSS) approach is presented for the blind estimation of multi-input multiple-output finite impulse response system. By exploiting the isomorphic relation between the input and output subspaces and the code sequences, this geometrical approach identifies the channel from a specially formed least squares smoothing error of the channel output. LSS has the finite sample convergence property, i.e., in the absence of noise, the channel is perfectly estimated with only a finite number of data samples. Referred to as the adaptive least squares smoothing algorithm, the adaptive implementation has a fast convergence rate. A-LSS is order recursive, and can be implemented using lattice filter and systolic array. It has the advantage that, when the channel order varies, channel estimates can be obtained without structural change of the implementation. For uncorrelated input sequence, the proposed algorithm performs direct deconvolution as a byproduct.

Paper Details

Date Published: 2 October 1998
PDF: 12 pages
Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); doi: 10.1117/12.325720
Show Author Affiliations
Qing Zhao, Univ of Connecticut (United States)
Lang Tong, Univ of Connecticut (United States)


Published in SPIE Proceedings Vol. 3461:
Advanced Signal Processing Algorithms, Architectures, and Implementations VIII
Franklin T. Luk, Editor(s)

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