A hybrid strategy for Gilbert's channel characterization using gradient and annealing techniques

Abstract

This paper presents a hybrid algorithm for estimating Gilbert's channel model parameters from an experimental error-gap distribution. A stochastic simulated annealing algorithm is applied to determine automatically a set of good starting points, which are then used by the deterministic gradient algorithm for faster convergence to the global optimum. Simulation results indicate that, for channel characterization, this hybrid strategy provides an ideal compromise between modelling accuracy and convergence time.