The massive proliferation of connected devices and the data they produce has had a ripple effect on attaining and sustaining high levels of mobile network performance. Service providers need new solutions to meet the growing demands placed on networks that are increasingly dense and diverse. Challenges to maximizing NQoS include:
Root-cause identification is often impeded by the inability to determine if an anomaly is caused by a problem with the device or the network. This leads to delayed mitigation and poor customer experience.
Network operators have difficulty in quantifying the impact of suboptimal radio signals on the user experience. This lack of insight can lead to reactions that are too heavy or too light.
The customer experience is negatively impacted by the unpredictably of roaming data availability and performance. This problem is compounded by the wide range of device types and their individual roaming behaviors.
via live NQoS Health Scores that allow operators to monitor network performance in real-time while also being able to filter data by equipment type, make, model, and location.
through monitoring and processing data related to physical radio signals received by the UE as well as user experience related inputs (ping, jitter, loss). Operators can quickly determine the level of impact on user experience.
via more direct measurement of the network experience of roaming users and creation of analytics that visualize and improve their experience.
MicroAI’s AI-enabled methodologies provide tangible NQoS differentiation for network operators, OEMs, and service providers. Positive impacts include:
