Abstract: A monitoring system and monitoring method for detecting a spectral anomaly in a cellular wireless network, in particular a 5G private uRLLC network, wherein an RF receiver monitors the cellular wireless network spectrum and derives spectrum and/or physical measurement values of the spectrum of the cellular wireless network, and a processing unit of the monitoring system executes a spectral anomaly neural network trained by a machine learning algorithm in a training system, wherein the processing unit obtains the spectrum and/or the physical measurement values of the spectrum and processes it to detect a spectral anomaly information.

Abstract: A system for prediction of network quality in a wireless network. The system comprises at least one mobile communication device, at least one data prediction unit and a data collection unit. Furthermore, the at least one mobile communication device measures the network quality and transmits the measured network quality to the data collection unit. In addition to this, the at least one data prediction unit calculates prediction data with respect to the network quality based on data from the data collection unit.

Abstract: An interface between a vehicle control system and a communication system is provided. The interface comprises an input configured to receive data from at least one of the vehicle control system and the communication system. The interface comprises a conversion layer configured to translate the received data into a format that is comprehensible to the other of the vehicle control system and the communication system. The interface also comprises an output configured to output the translated data to the other of the vehicle control system and the communication system. This enables both the vehicle control system and communication system to understand the other while still retaining their individual autonomy.

Abstract: A monitoring system and monitoring method for detecting a spectral anomaly in a cellular wireless network, in particular a 5G private uRLLC network, wherein an RF receiver monitors the cellular wireless network spectrum and derives spectrum and/or physical measurement values of the spectrum of the cellular wireless network, and a processing unit of the monitoring system executes a spectral anomaly neural network trained by a machine learning algorithm in a training system, wherein the processing unit obtains the spectrum and/or the physical measurement values of the spectrum and processes it to detect a spectral anomaly information.

Abstract: A wireless communication device comprises: a transceiver being configured to measure a plurality of interference powers associated with a plurality of radio resources; and a processor being configured to determine, on the basis of the plurality of interference powers, conflicting radio resources of the wireless communication device. The transceiver is further configured to transmit data identifying the conflicting radio resources of the wireless communication device to at least one other wireless communication device and to receive data identifying conflicting radio resources of the at least one other wireless communication device.

Abstract: An interface between a vehicle control system and a communication system is provided. The interface comprises an input configured to receive data from at least one of the vehicle control system and the communication system. The interface comprises a conversion layer configured to translate the received data into a format that is comprehensible to the other of the vehicle control system and the communication system. The interface also comprises an output configured to output the translated data to the other of the vehicle control system and the communication system. This enables both the vehicle control system and communication system to understand the other while still retaining their individual autonomy.

Abstract: A system for prediction of network quality in a wireless network. The system comprises at least one mobile communication device, at least one data prediction unit and a data collection unit. Furthermore, the at least one mobile communication device measures the network quality and transmits the measured network quality to the data collection unit. In addition to this, the at least one data prediction unit calculates prediction data with respect to the network quality based on data from the data collection unit.

Abstract: A wireless communication device comprises: a transceiver being configured to measure a plurality of interference powers associated with a plurality of radio resources; and a processor being configured to determine, on the basis of the plurality of interference powers, conflicting radio resources of the wireless communication device. The transceiver is further configured to transmit data identifying the conflicting radio resources of the wireless communication device to at least one other wireless communication device and to receive data identifying conflicting radio resources of the at least one other wireless communication device.