A novel stopping criterion for turbo codes based on the average a posteriori entropy

In this paper, we treat the turbo decoding algorithm as a dynamical system parameterized by a single parameter that closely approximates the signal-to-noise ratio (SNR). A whole range of phenomena known to occur in nonlinear systems, like the existence of multiple fixed points, oscillatory behavior, bifurcations, chaos and transient chaos are found in the turbo decoding algorithm. As an application, we developed a novel stopping criterion based on the average entropy of an information block and proposed an adaptive strategy as a function of the SNR.