Exploring the Dynamics of Data Transmission in 5G Networks: A Conceptual Analysis
Nikita Smirnov, Sven Tomforde

TL;DR
This paper analyzes data transmission dynamics in 5G networks for remote-controlled ferries, evaluating protocols, network issues, and adaptive solutions through simulations and real-world experiments to optimize real-time communication.
Contribution
It introduces open-source tools for 5G and WebRTC experiments, formulates bandwidth and latency requirements, and compares traditional and AI-based adaptive communication methods.
Findings
H.264 hardware codec performs best among tested codecs.
AI-based adaptive communication outperforms traditional algorithms in key metrics.
Simulation and real-world tests provide bandwidth and latency estimates for reliable 5G data transmission.
Abstract
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…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization
