Delay reduction techniques for playout buffering
IEEE Transactions on Multimedia
Adaptive playout scheduling and loss concealment for voice communication over IP networks
IEEE Transactions on Multimedia
Internet telephony: going like crazy
IEEE Spectrum
Intelligent voice smoother for silence-suppressed voice over Internet
IEEE Journal on Selected Areas in Communications
Characterizing Superposition Arrival Processes in Packet Multiplexers for Voice and Data
IEEE Journal on Selected Areas in Communications
Neural and fuzzy computation techniques for playout delay adaptation in VoIP networks
IEEE Transactions on Neural Networks
A survey of packet loss recovery techniques for streaming audio
IEEE Network: The Magazine of Global Internetworking
Hi-index | 0.00 |
Network delay, packet loss and network delay variability (jitter) are important factors that impact on perceived voice quality in VoIP networks. An adaptive playout buffer is used in a VoIP terminal to overcome jitter. Such a buffer-control must operate a trade-off between the buffer-induced delay and any additional packet loss rate. In this paper, a Garch-based adaptive playout algorithm is proposed which is capable of operating in both inter-talkspurt and intra-talkspurt modes. The proposed new model is based on a Garch model approach; an ARMA model is used to model changes in the mean and the variance. In addition, a parameter estimation procedure is proposed, termed Direct Garch whose cost function is designed to implement a desired packet loss rate whilst minimising the probability of consecutive packet losses occurring. Simulations were carried out to evaluate the performance of the proposed algorithm using recorded VoIP traces. The main result is as follows; given a target Packet Loss Rate (PLR) the Direct Garch algorithm produces parameter estimates which result in a PLR closer than other algorithms. In addition, the proposed Direct Garch algorithm offers the best trade-off between additional buffering delay and Packet Loss Rate (PLR) compared with other traditional algorithms.