AI-aided Wireless Systems for Mobility in Industry and Traffic
About the Project AI4Mobile
The project AI4Mobile is a research project funded by the Federal Ministry for Education and Research (BMBF), from the announcement
Artificial Intelligence in Communication Networks within the scope of the High-Tech Strategy of the German Federal Government.
Powerful and flexible mobile networks are a key technology for numerous branches of industry. Many applications, for example in the fields of automated vehicles or mobile robotics, are highly dynamic and mobile. At the same time, they require extremely reliable communication with low latency. An important challenge is to ensure the required quality of service (e.g. a reliable data rate, no data loss, no delays) for each application. The wireless transmission of information is by nature subject to interference, which means that successful real-time transmission in classic, reactive mobile radio systems cannot be guaranteed. Forward planning of network resources and prediction of relevant quality of service parameters are therefore essential, especially for safety-critical functions. Given the immense complexity of the overall network, methods of artificial intelligence (AI) offer a promising approach here.
Goals and Procedure
The project AI4Mobile aims at developing methods that enable a robust prediction of the quality of service at high mobility using data from the entire mobile network. In combination with other data (application, environment and network data) the predicted quality of service information will be used to develop AI mechanisms for real-time network optimization. AI methods are particularly promising for resource management. In order to make use of existing knowledge in the field of mobile communications, the possibility of supplementing AI approaches with area-specific context information and of integrating expert knowledge into the design of learning processes will be investigated. This will enable a hybrid approach of classical algorithm development and artificial intelligence. The project investigates to what extent this approach can increase the security and robustness of mobile networks.
Innovations and Perspectives
The AI4Mobile solution can be used to predict critical quality of service parameters (e.g. data rate, delay) of a complete communication link between sender and receiver. This allows the implementation of proactive resource optimization and networking in all parts of the mobile infrastructure. An early detection of critical states ensures that the performance of the systems is maintained even if undefined states and faults occur. The security and robustness of the mobile radio network is significantly increased, which is essential for dynamic applications such as automated driving or mobile robotics. The project thus contributes to consolidating Germany's technological leadership, especially in the important automotive and industry 4.0 sectors.
The Berlin V2X dataset offers high-resolution GPS-located wireless measurements across diverse urban environments in the city of Berlin for both cellular and sidelink radio access technologies, acquired with up to 4 cars over 3 days. The data enables thus a variety of different ML studies towards vehicle-to-anything (V2X) communication.
This measurement campaign was conducted for around 16h at an industrial site where an autonomous cleaning robot collected sensor data from the environment and communicated with a private cellular network.
All vehicles are equipped with devices that generate background data traffic.
Various features from all parts of the communication system are recorded with a high temporal resolution, resulting in hundreds of megabytes of data.
In October 2020, the first measurement campaign of the project was conducted at the Motorway A9 5G-ConnectedMobility measurement site near Nuremberg, Germany.
Measurements were conducted on five consecutive days with four vehicles travelling a total distance of 3300km.
At the measurement site, five base stations with two sectors each cover motorway, rural, and suburban areas. The non-public network is operated at 700MHz.
Mobile devices in each vehicle use dedicated software to generate data traffic and collect measurements.
Various features from all parts of the communication system are recorded with a high temporal resolution, resulting in several terabytes of data.
All vehicles are equipped with additional mobile devices that generate background data traffic.
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