Low-Latency Network-Adaptive Error Control for Interactive Streaming

TL;DR

This paper presents a real-time adaptive error correction algorithm and new streaming codes that improve low-latency interactive audio streaming by effectively handling packet losses and reducing jitter.

Contribution

It introduces a novel network-adaptive algorithm that dynamically optimizes streaming code parameters and provides a new explicit construction of low-latency streaming codes with optimal loss correction tradeoffs.

Findings

Significantly higher performance over UDP with adaptive coding.

Explicit streaming codes outperform traditional MDS codes.

Adaptive algorithm effectively reduces jitter and packet loss effects.

Abstract

We introduce a novel network-adaptive algorithm that is suitable for alleviating network packet losses for low-latency interactive communications between a source and a destination. Our network-adaptive algorithm estimates in real-time the best parameters of a recently proposed streaming code that uses forward error correction (FEC) to correct both arbitrary and burst losses, which cause a crackling noise and undesirable jitters, respectively in audio. In particular, the destination estimates appropriate coding parameters based on its observed packet loss pattern and sends them back to the source for updating the underlying code. Besides, a new explicit construction of practical low-latency streaming codes that achieve the optimal tradeoff between the capability of correcting arbitrary losses and the capability of correcting burst losses is provided. Simulation evaluations based on statistical losses and real-world packet loss traces reveal the following: (i) Our proposed network-adaptive algorithm combined with our optimal streaming codes can achieve significantly higher performance compared to uncoded and non-adaptive FEC schemes over UDP (User Datagram Protocol); (ii) Our explicit streaming codes can significantly outperform traditional MDS (maximum-distance separable) streaming schemes when they are used along with our network-adaptive algorithm.