Low computational complexity adaptive equalization algorithm for time-variety underwater acoustic channels

The performance of equalization algorithm on different channels is sensitive to the choice of step-size or forgetting factor. To overcome this problem, self-optimized algorithm may be used, but this results in increased complexity. A new equalization algorithm was proposed which had an algorithm transition under a mean square error (MSE) rule. Simulation results on different underwater acoustic channels show that, unsuitable step-size causes algorithm diverge, while the approach has robust convergence performance. At the same time it can decrease 30% computation complexity compared with FOLMS algorithm. This algorithm is particularly suitable for real-time implementation under time-variety underwater acoustic channels for its low computational load and self-adaptive behavior.