The ORD-based least squares lattice algorithm: Some computer simulations using finite wordlengths

Abstract
The QR-decomposition (QSD)-based least-squares lattice algorithm and its architecture are described. This algorithm can be used to solve least-squares minimization problems that involve time-series data. The results of some computer simulation experiments on an adaptive channel equalizer using the QRD-based lattice algorithm are presented. These simulations were performed using limited-precision floating-point arithmetic. The results show that very little penalty is paid in reducing the computational load. The QRD-based lattice algorithm works essentially as well as the QRD-based triangular systolic array but requires only O(p/sup 2/N) operations per time instant as compared with O(p/sup 2/N/sup 2/) for the array. The results also confirm that a square-root-free form of the algorithm is empirically better than the standard form.

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