Abstract: Various techniques for analyzing data networks with impaired network components, recording network telemetry data and labeling the information for use in training one or more machine learning algorithms is described. The machine learning algorithms trained in this way are used to detect impaired network components and/or noise on operational data networks.

Abstract: Various techniques for analyzing data networks with impaired network components, recording network telemetry data, labeling the information, and retrieving the information is described.

Abstract: Various techniques include detecting noise in a network, identifying the type of noise in the network, localizing noise in the network, determining noise scores for network devices, and/or determining likelihoods that particular devices are causing noise and/or are in proximity of a point of entry of noise into the network.

Abstract: Various techniques include identifying and prioritizing fixing impairments in networks to reduce negative impacts on the network.

Abstract: Various devices and techniques help to reduce the entry of unwanted radio waves into an enclosure and reduce the reflection of radio waves inside the enclosure. Such devices and techniques enable a test environment inside the enclosure that provides high-quality functionality and performance testing.

Abstract: Various devices and techniques help to reduce the entry of unwanted radio waves into an enclosure and reduce the reflection of radio waves inside the enclosure. Such devices and techniques enable a test environment inside the enclosure that provides high-quality functionality and performance testing.

Abstract: Various techniques include identifying impairments in networks, prioritizing the impairments, and prioritizing fixing the impairments to reduce negative impacts on network customers.

Abstract: Various techniques include detecting noise in a network, identifying the type of noise in the network, localizing noise in the network, determining noise scores for network devices, and/or determining likelihoods that particular devices are causing noise and/or are in proximity of a point of entry of noise into the network.

Abstract: The present disclosure relates generally to network diagnostics, and more specifically to techniques for determining the health of customer premises equipment (CPE) devices. In certain examples, a scoring system can determine a health score for a CPE device, the health score indicating the health of the CPE device. The health score is determined by receiving, analyzing, and integrating information from different sources, including sources in addition to CPE diagnostic data for the CPE device at the current time. Such sources can include CPE diagnostic data for the CPE device at other times, CPE diagnostic data for other CPE devices related to the CPE device (e.g., in the same household or surrounding area as the CPE device), technical specifications of the CPE device (e.g., make, model and firmware of the CPE device), or per-equalization parameters obtained by the CPE device.

Abstract: An impairment in a network is identified and information (e.g., frequency noise ingress and/or signal leakage and/or location in the network) about the impairment is determined, thereby enabling a network operator to quickly and accurately find, prioritize, and repair network impairments.

Abstract: Various techniques for analyzing data networks with impaired network components, recording network telemetry data and labeling the information for use in training one or more machine learning algorithms is described. The machine learning algorithms trained in this way are used to detect impaired network components and/or noise on operational data networks.

Abstract: Various devices and techniques help to reduce the entry of unwanted radio waves into an enclosure and reduce the reflection of radio waves inside the enclosure. Such devices and techniques enable a test environment inside the enclosure that provides high-quality functionality and performance testing.

Abstract: The present disclosure relates generally to network diagnostics, and more specifically to techniques for determining the health of customer premises equipment (CPE) devices. In certain examples, a scoring system can determine a health score for a CPE device, the health score indicating the health of the CPE device. The health score is determined by receiving, analyzing, and integrating information from different sources, including sources in addition to CPE diagnostic data for the CPE device at the current time. Such sources can include CPE diagnostic data for the CPE device at other times, CPE diagnostic data for other CPE devices related to the CPE device (e.g., in the same household or surrounding area as the CPE device), technical specifications of the CPE device (e.g., make, model and firmware of the CPE device), or per-equalization parameters obtained by the CPE device.

Abstract: Various techniques include detecting noise in a network, identifying the type of noise in the network, localizing noise in the network, determining noise scores for network devices, and/or determining likelihoods that particular devices are causing noise and/or are in proximity of a point of entry of noise into the network.

Abstract: Various techniques include identifying impairments in networks, prioritizing the impairments, and prioritizing fixing the impairments to reduce negative impacts on network customers.

Abstract: Various devices and techniques help to reduce the entry of unwanted radio waves into an enclosure and reduce the reflection of radio waves inside the enclosure. Such devices and techniques enable a test environment inside the enclosure that provides high-quality functionality and performance testing.

Abstract: Various techniques include detecting noise in a network, identifying the type of noise in the network, localizing noise in the network, determining noise scores for network devices, and/or determining likelihoods that particular devices are causing noise and/or are in proximity of a point of entry of noise into the network.

Abstract: Various techniques include identifying impairments in networks, prioritizing the impairments, and prioritizing fixing the impairments to reduce negative impacts on network customers.

Abstract: Various techniques include detecting noise resulting from data network impairments and analyzing the noise to determine a likely source and location of the data network impairments. The analysis is used to generate noise reports that instruct network technicians how to check network devices for network impairments. The instructions can be provided on portable electronic devices that are further configured to receive data characterizing any impairments identified at the network devices. The data generated by the network technicians can be used to improve the ability of the techniques to correctly identify the source of data network impairments.

Abstract: A variety of device interfaces may be connected to a test platform in a fast and efficient manner using multi-pin cables and connectors to support high-volume processing of devices to be tested. The multi-pin cables and connectors may aggregate a plurality of specific device interfaces into a single cable that can be connected via a connector to a test shelf and via a connector to a test platform, reducing the time to setup for device testing and facilitating high-volume processing of devices to be tested.