Wireless Communication Network Voice Quality Monitoring

    公开(公告)号:US20240214844A1

    公开(公告)日:2024-06-27

    申请号:US18288466

    申请日:2021-05-10

    摘要: 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.

    Method for generating a quality of experience (QoE) index by way of ensemble of expectation scores

    公开(公告)号:US12015531B2

    公开(公告)日:2024-06-18

    申请号:US17541432

    申请日:2021-12-03

    申请人: GUAVUS, Inc.

    发明人: Kuldeep Jiwani

    摘要: A method provides telecom operators a single Quality of Experience (QoE) index to collectively interpret service experience and network experience by way of ensemble of expectation scores. The method includes the steps of mapping Key Performance Indicators (KPIs) of time-series data into multiple probability spaces of statistical expectation functions thereby producing time-series expectation scores; applying vector geometry to said time-series expectation scores for each of said statistical expectation functions thereby producing an N-Dimensional probability vector; normalizing correlations of said N-Dimensional probability vector across said KPIs thereby producing a normalized N-Dimensional probability vector; and generating a N-Dimensional probability distribution from the normalized N-Dimensional probability vector to produce an ensemble function. The ensemble function is then be applied to time-series data thereby producing an ensemble index, which represents the QoE (Quality of Experience).

    System and method for dynamic time estimates

    公开(公告)号:US11924063B2

    公开(公告)日:2024-03-05

    申请号:US18109233

    申请日:2023-02-13

    申请人: PAYPAL, INC.

    摘要: Aspects of the present disclosure involve systems, methods, devices, and the like for obtaining real-time estimates. In one embodiment, a novel customizable, transferable system architecture is presented that enables the characterization of a task, designated for time estimate, into steps or processes. The characterization may occur using the novel architecture which introduces an estimates service module that can provide an initial timing estimate by obtaining a composite time estimate of all steps. Timing of each of the steps can be predicted using a job scheduling enterprise designed to model the job or step. In another embodiment, delays are captured by time estimate monitors which can provide the alerts and delta time differences. Such alerts and time differences can be updated and presented to the user.