Pipelining extended givens rotation RLS adaptive filters

In this paper, we propose a new pipelining extended Givens Rotation Recursive Least Square (PEGR-RLS) architecture using look-ahead technique. The square-root-free forms of QRD-RLS are also difficult to pipeline. The PEGR-RLS algorithm (referred to as Scaled Tangent Rotation, STAR-RLS) is designed s...

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Bibliographic Details
Main Authors: Shing Tenqchen, Ji-Horn Chang, Wu-Shiung Feng, Bor-Sheng Jeng
Format: Conference Proceeding
Language:English
Subjects:
Adaptive filters
Algorithm design and analysis
Delay
Equalizers
Hardware
Least squares approximation
Pipeline processing
Resonance light scattering
Roentgenium
Systolic arrays
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Summary:In this paper, we propose a new pipelining extended Givens Rotation Recursive Least Square (PEGR-RLS) architecture using look-ahead technique. The square-root-free forms of QRD-RLS are also difficult to pipeline. The PEGR-RLS algorithm (referred to as Scaled Tangent Rotation, STAR-RLS) is designed such that fine-grain pipelining can be accomplished with little hardware overhead. Similar to STAR-RLS, this algorithm is not exactly orthogonal transformations but tends to become orthogonal asymptotically. This algorithm also preserves the desired properties of the STAR-RLS algorithm. Specifically, it can be pipelined at very low forgetting factor by using extended look-ahead. Simulation results are presented to compare the performance of the STAR-RLS, QRD-RLS, and LMS algorithms.
DOI:10.1109/DELTA.2002.994675