Joint Optimization of Buffer Delay and HARQ for Video Communications

TL;DR

Problem: QoE deterioration in real-time video over lossy networks due to packet loss and latency. Approach: BD-HARQ jointly optimizes dynamic buffer delay $d$ and HARQ redundancy $r$, deriving a closed-form recovery rate $\xi$ via $\xi = \Phi\left( \frac{mr-\mu_a}{\sigma_a} \right)$ from a Gaussian model of total losses and solving for optimal $(r,d)$ with discretized exhaustive search. Contributions: (i) a QoE-driven, piecewise-linear evaluation with $Q = h_{D}Q_{D} + h_{R}Q_{R} + h_{\Xi}Q_{\Xi}$; (ii) analytic relationships among $d$, $r$, and $\xi$ based on RS FEC and loss distributions; (iii) experimental validation showing up to 13.7% QoE gain and improved loss tolerance up to 31%. Significance: enables real-time, robust video transmission over lossy networks by balancing latency, redundancy, and data-recovery probability.

Abstract

To improve the quality of experience (QoE) in video communication over lossy networks, this paper presents a transmission method that jointly optimizes buffer delay and Hybrid Automatic Repeat request (HARQ), referred to as BD-HARQ. This method operates on packet group and employs dynamic buffer delay combined with HARQ strategy for transmission. By defining the QoE based on metrics such as buffer delay, Forward Error Correction (FEC) redundancy, and data recovery rate, the proposed method derives its closed-form expression through rigorous mathematical modeling and analysis. The optimal transmission parameters, i.e., the buffer delay and the FEC redundancy, are then determined and implemented, guaranteeing the real-time performance, transmission efficiency, and data recovery rate of video communication. Experimental results demonstrate that the proposed method aligns well with its theoretical expectations, and that it can provide up to 13.7% higher QoE compared to existing methods and increase the tolerance for packet loss rate from 15%-22% to up to 31% while maintaining a high QoE.

Figures (5)

• Figure 1: System Model of the BD-HARQ Method
• Figure 2: Relationship Between Recovery Rate and Redundancy Under Different Buffer Delays
• Figure 3: Relationship Between Recovery Rate and Packet Loss Rate Under Different Redundancies
• Figure 4: Comparison of QoE for Different Transmission Methods
• Figure 5: Comparison of Detailed Metrics for Different Transmission Methods