Optimizing 5G-Advanced Networks for Time-critical Applications: The Role of L4S

TL;DR

The experimental results show that the proposed L4S-GCC algorithm can reduce the stalling rate by 1.51-2.80 percent and increase the bandwidth utilization by 11.4-31.4 percent, emphasizing the immense potential of L4S technology in enhancing transmission performance in time-critical applications.

Abstract

As 5G networks strive to support advanced time-critical applications, such as immersive Extended Reality (XR), cloud gaming, and autonomous driving, the demand for Real-time Broadband Communication (RTBC) grows. In this article, we present the main mechanisms of Low Latency, Low Loss, and Scalable Throughput (L4S). Subsequently, we investigate the support and challenges of L4S technology in the latest 3GPP 5G-Advanced Release 18 (R18) standard. Our case study, using a prototype system for a real-time communication (RTC) application, demonstrates the superiority of L4S technology. The experimental results show that, compared with the GCC algorithm, the proposed L4S-GCC algorithm can reduce the stalling rate by 1.51%-2.80% and increase the bandwidth utilization by 11.4%-31.4%. The results emphasize the immense potential of L4S technology in enhancing transmission performance in time-critical applications.

Figures (3)

• Figure 1: Illustration of L4S Technology Principle. The left figure represents the classic transport model, and the right figure shows the L4S-based transport model.
• Figure 2: Schematic diagram of L4S in the 5G-Advanced.
• Figure 3: System architecture for L4S-based RTC application.