Correlation-based fast training of data-driven Nyquist in-band echo cancellers

Abstract

A novel echo canceller fast training scheme for data-driven 'Nyquist' in-band echo cancellers is presented. This scheme simultaneously estimates the near and far echo canceller coefficients by sending a special periodic training sequence and correlating a segment of the sequence with the real echo samples of the sequence. The requirements and the generation of such a training sequence are discussed and described in detail. Fast initialization of a phase-roll compensator is also discussed. The proposed scheme is compared with other echo canceller training schemes.<>