This conceptual analysis examines the dynamics of data transmission in 5G
networks. It addresses various aspects of sending data from cameras and LiDARs
installed on a remote-controlled ferry to a land-based control center. The
range of topics includes all stages of video and LiDAR data processing from
acquisition and encoding to final decoding, all aspects of their transmission
and reception via the WebRTC protocol, and all possible types of network
problems such as handovers or congestion that could affect the quality of
experience for end-users. A series of experiments were conducted to evaluate
the key aspects of the data transmission. These include simulation-based
reproducible runs and real-world experiments conducted using open-source
solutions we developed: "Gymir5G" - an OMNeT++-based 5G simulation and
"GstWebRTCApp" - a GStreamer-based application for adaptive control of media
streams over the WebRTC protocol. One of the goals of this study is to
formulate the bandwidth and latency requirements for reliable real-time
communication and to estimate their approximate values. This goal was achieved
through simulation-based experiments involving docking maneuvers in the Bay of
Kiel, Germany. The final latency for the entire data processing pipeline was
also estimated during the real tests. In addition, a series of simulation-based
experiments showed the impact of key WebRTC features and demonstrated the
effectiveness of the WebRTC protocol, while the conducted video codec
comparison showed that the hardware-accelerated H.264 codec is the best.
Finally, the research addresses the topic of adaptive communication, where the
traditional congestion avoidance and deep reinforcement learning approaches
were analyzed. The comparison in a sandbox scenario shows that the AI-based
solution outperforms the WebRTC baseline GCC algorithm in terms of data rates,
latency, and packet loss.

利用实验和模拟研究，本论文探讨了 5G 网络中数据传输的动态过程，包括视频和 LiDAR 数据处理的各个阶段，数据的传输和接收，以及与网络问题相关的用户体验质量。此外，论文还研究了可靠实时通信的带宽和延迟需求，并通过实验估计了相关数值。最后，作者还比较了自适应通信方案与 WebRTC 基准 GCC 算法的性能差异。

探索 5G 网络数据传输动力学：概念分析

Exploring the Dynamics of Data Transmission in 5G Networks: A Conceptual  Analysis

In real-world multi-agent systems, agents with different capabilities may
join or leave without altering the team's overarching goals. Coordinating teams
with such dynamic composition is challenging: the optimal team strategy varies
with the composition. We propose COPA, a coach-player framework to tackle this
problem. We assume the coach has a global view of the environment and
coordinates the players, who only have partial views, by distributing
individual strategies. Specifically, we 1) adopt the attention mechanism for
both the coach and the players; 2) propose a variational objective to
regularize learning; and 3) design an adaptive communication method to let the
coach decide when to communicate with the players. We validate our methods on a
resource collection task, a rescue game, and the StarCraft micromanagement
tasks. We demonstrate zero-shot generalization to new team compositions. Our
method achieves comparable or better performance than the setting where all
players have a full view of the environment. Moreover, we see that the
performance remains high even when the coach communicates as little as 13% of
the time using the adaptive communication strategy.

提出 COPA 框架应对动态团队组合，使用注意力机制协调教练具有全局视图和只能看到部分视图的玩家，通过分配个体策略和自适应通信方法，验证了方法在资源收集任务、救援游戏和星际争霸微观管理任务上的性能。