Title :
Adaptive least squares smoothing for blind channel estimation and tracking
Author :
Zhao, Qing ; Tong, Lang
Author_Institution :
Dept. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
Abstract :
A least squares smoothing (LSS) approach is presented for the blind estimation of single-input multiple-output finite impulse response systems. By exploiting the isomorphic relation between the input and output subspaces, this geometrical approach identifies the channel from the least squares smoothing error of the channel output. Based on this approach, an adaptive least squares smoothing (A-LSS) algorithm is proposed. Compared with subspace and linear prediction-based algorithms, A-LSS gains an advantage for its high convergence rate, adaptivity to both channel order and channel parameter variation, low complexity with no matrix operations, and modular structure suitable for VLSI implementation
Keywords :
FIR filters; adaptive equalisers; adaptive filters; adaptive signal processing; blind equalisers; convergence of numerical methods; least squares approximations; parameter estimation; smoothing methods; tracking; VLSI implementation; adaptive least squares smoothing; blind channel estimation; channel order; channel parameter variation; complexity; convergence rate; finite impulse response systems; isomorphic relation; modular structure; single-input multiple-output systems; smoothing error; tracking; Blind equalizers; Channel estimation; Contracts; Convergence; Least squares approximation; Least squares methods; Smoothing methods; Throughput; Vectors; Very large scale integration;
Conference_Titel :
Statistical Signal and Array Processing, 1998. Proceedings., Ninth IEEE SP Workshop on
Conference_Location :
Portland, OR
Print_ISBN :
0-7803-5010-3
DOI :
10.1109/SSAP.1998.739389
