Affine projection methods in fault tolerant adaptive filtering

Reliable performance is very important for high speed channel equalizers and echo cancellers used in high speed communications channels. A common type of hardware fault occurs when the coefficients get “stuck” at an uncontrollable value. Such faults lead to larger overall mean square errors, and generally poor performance. Redundancy can provide the ability to compensate for these types of faults if the proper design is introduced into the adaptive filter structure. Unfortunately this form of redundancy can lead to poor convergence performance for the adaptive filter after the fault occurrence. This paper examines the use of affine projection and row projection techniques to improve the convergence performance of the fault tolerant adaptive filtering structure. Algorithms are developed for two cases: fault knowledge and no fault knowledge incorporated in the adaptive filtering update. These algorithms are introduced in this paper and simulations are presented to illustrate the effectiveness of these approaches