WIRELESS COMMUNICATION NETWORK VOICE QUALITY MONITORING

• Main Authors: MITCSENKOV, Attila, SÁFÁR, Orsolya, BRÁJER, Attila
• Format: Patent
• Language: English; French; German
• Published: 20.03.2024
• Subjects: ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION; WIRELESS COMMUNICATIONS NETWORKS

In voice communication quality monitoring, both user plane and control plane signaling are gathered during network operation, and correlated. Offline (that is, not in real time), a predictive machine learning model is trained using the signaling data. The model is subsequently used to monitor network operation in real time. The model label is instances of voice quality degradation gleaned from probing the user plane media. The are control plane traffic patterns correlated to the voice quality degradation incidents. After training, when monitoring voice quality in real time on the network, only the control plane signaling is monitored. The machine learning model recognizes learned control plane signaling patterns and infers corresponding user plane voice quality degradation incidents. Settings of the model are controlled to achieve a desired precision/recall tradeoff. Because only control plane signaling is monitored in real time, the approach can be applied across all voice communications in a network (or portion of a network). The machine learning model is re-trained as necessary to reflect changes in the network.