Adaptive VoIP Smoothing of Pareto Traffic Based on Optimal E-Model Quality

Abstract

Perceived voice quality is a key metric for VoIP applications. It is mainly affected by IP network impairments such as delay, jitter and packet loss. Adaptive smoothing algorithms are capable of adjusting dynamically the smoothing size by introducing a variable delay based on the network delay and loss parameters to archive the best voice quality. This work formulates an online loss model which incorporates buffer sizes and introduces an efficient and feasible perceived quality method for buffer optimization. Distinct from the other optimal smoothers, the proposed optimal smoother suitable for most of codecs carries the lowest complexity. Since the adaptive smoothing scheme introduces variable playback delays, the buffer re-synchronization between the capture and the playback becomes essential. This work also presents a buffer re-synchronization algorithm to prevent unacceptable increase in the buffer overflow. Simulation experiments validate that the proposed adaptive smoother archives significant improvement in the voice quality.