# Ad-BBR: Enhancing Round-Trip Time Fairness and Transmission Stability in TCP-BBR
## 5 Experiment and Evaluation
### Throughput  
To assess whether the Ad-BBR algorithm achieves superior throughput performance, this experiment measures the average throughput and latency of each algorithm using the NS3 simulator. Packet loss rates are set to 0%, 10%, and 20%, and the bottleneck buffers are configured to 0.5 BDP and 5 BDP. Experiments are conducted for each algorithm under six different conditions, and the simulation results are presented in Figure 5.  
The experimental results show that as the packet loss rate increases, the throughput of each congestion control algorithm decreases and the delay increases, while increasing the buffer size leads to higher throughput but also greater delay. Packet loss-based congestion control algorithms, such as Cubic and Reno, typically exhibit low throughput and high delay. These algorithms rely on packet loss as a congestion signal; when a loss is detected, they reduce the congestion window and sacrifice throughput. Moreover, they tend to fill the buffer until packet loss occurs, which further increases delay, especially with larger buffers. The BBRv1 algorithm consistently achieves high throughput in most scenarios,  
Figure 4: Experimental network topology of the NS3.  
but its latency performance is poor. In contrast, while the BBRv3 and BBQ algorithms perform well under normal conditions, both their throughput and latency deteriorate under high-packet-loss scenarios. In contrast, the Ad-BBR algorithm demonstrates stable and robust throughput across various environments, particularly under high-packet-loss conditions, indicating superior packet loss tolerance. Furthermore, Ad-BBR consistently ranks among the top three in terms of latency performance. Overall, the Ad-BBR algorithm maintains strong performance compared to all other algorithms when packet loss rates or buffer sizes vary. For instance, while its throughput may be slightly lower than that of some algorithms, its latency performance is superior, and it sustains high throughput even when latency is marginally compromised.  
Additionally, this experiment configures bottleneck buffers of 0.5 BDPs and 5 BDPs in 5G and Wi-Fi network simulations. A 5 Gbps file is downloaded over a TCP link controlled by different congestion algorithms, and the download rates are recorded. The results are presented in Figures 6 and 7.  
In both 5G and Wi-Fi environments, increasing the buffer size leads to higher download rates for all algorithms. Notably, BBR-based algorithms achieve significantly greater throughput than packet loss-based algorithms such as Cubic and Reno, particularly in 5G scenarios, where BBR-based algorithms consistently outperform Cubic and Reno. This advantage likely stems from the fact that BBR-based algorithms do not rely solely on packet loss for congestion detection; instead, they perform congestion control by continuously measuring the bandwidth-delay product (BDP) in real time, making them better suited for high-speed wireless networks characterized by abundant bandwidth, random packet loss, and considerable delay fluctuations. Among all evaluated algorithms, Ad-BBR exhibits outstanding performance by achieving download rates that are approximately 17% higher than those of the original BBRv1 and 26% higher than those of BBRv3, an improved version of BBRv1.