Artificial Intelligence (AI) can rapidly evaluate a faulted message in 5G or 6G, calculate a likelihood that each message element is faulted, and optionally suggest a most probable corrected version for each of the likely faulted message elements. To do so, the AI takes in numerous factors besides the message itself, such as the modulation quality of each message element, the proximity and quality of a nearest demodulation reference, a signal-to-noise ratio of the message element, a measure of current electromagnetic noise during the message element, an expected format or expected codewords based on prior messages or convention, and other factors. The AI model can then provide guidance as to mitigation, such as choosing whether to request a retransmission or attempting to vary the likely faulted message elements. The AI model can be adapted to fixed-site computers or to the more limited computers of a mobile user device.

Aspects of the disclosure relate to a user equipment (UE) configured to schedule resource management procedures including measurements and tracking loop procedures. In some examples, the UE includes at least one antenna pair and two or more receivers. The UE may be configured to determine a plurality of combinations of antenna pairs and component carriers, where each component carrier is associated with a particular frequency. The UE may further be configured to schedule measurements/tracking loop procedures to available receivers first and utilize a selection algorithm to select combinations of antenna pairs and component carriers and map the selected combinations to the remaining of the available receivers to perform tracking loop procedures. Other aspects, features, and embodiments are also claimed and described.

Aspects of the disclosure relate to a user equipment (UE) configured to schedule resource management procedures including measurements and tracking loop procedures. In some examples, the UE includes at least one antenna pair and two or more receivers. The UE may be configured to determine a plurality of combinations of antenna pairs and component carriers, where each component carrier is associated with a particular frequency. The UE may further be configured to schedule measurements/tracking loop procedures to available receivers first and utilize a selection algorithm to select combinations of antenna pairs and component carriers and map the selected combinations to the remaining of the available receivers to perform tracking loop procedures. Other aspects, features, and embodiments are also claimed and described.

A test kit for testing a device under test (DUT) includes a socket structure for containing the DUT. The DUT includes an antenna and radiates a RF signal. The test kit further includes a reflector having a lower surface. The RF signal emitted from the antenna of the DUT is reflected by the reflector and a reflected RF signal is received by the antenna of the DUT.

A test kit for testing a device under test (DUT) includes a socket structure for containing the DUT. The DUT includes an antenna and radiates a RF signal. The test kit further includes a reflector having a lower surface. The RF signal emitted from the antenna of the DUT is reflected by the reflector and a reflected RF signal is received by the antenna of the DUT.

The disclosed system defines a hierarchical subdivision of a geographic area including a unit, a cluster, a region, and an area, where the area includes multiple regions, the region includes multiple clusters, and the cluster includes multiple units. The system obtains KPIs associated with a unit and obtains a network score for the cluster by combining each KPI associated with each unit in the cluster. The system obtains a competitor network score associated with a competing network. Based on the competitor network score and the network score, the system can determine whether the cluster, the region, and the area are performing satisfactorily.

An eye diagram is generated for a digital interface, such as a Serializer/Deserializer (SerDes) interface. A probability map is captured by stepping through a fixed sequence of phase and reference voltage levels and counting a number of highs or lows. The switching of phase includes merely increasing the phase difference rather than performing complex phase/data analysis. The probability map can then be used to generate an eye diagram through simple differentiation. For example, the differentiation between various pixel locations in the probability map can be used to yield the edges of the eye in an eye diagram. The standard Serdes parameters can then be extracted from the eye diagram. The parameters can then be used to determine if the serial connection is problematic.

An eye diagram is generated for a digital interface, such as a Serializer/Deserializer (SerDes) interface. A probability map is captured by stepping through a fixed sequence of phase and reference voltage levels and counting a number of highs or lows. The switching of phase includes merely increasing the phase difference rather than performing complex phase/data analysis. The probability map can then be used to generate an eye diagram through simple differentiation. For example, the differentiation between various pixel locations in the probability map can be used to yield the edges of the eye in an eye diagram. The standard Serdes parameters can then be extracted from the eye diagram. The parameters can then be used to determine if the serial connection is problematic.

Systems for self-organizing data collection and storage in a manufacturing environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the manufacturing system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.

Systems, methods, and computer-readable media herein dynamically adjust the number of elements active within a neighboring base station in order to reduce the back lobe overlap and thus reduce the interference caused by such an overlap. User devices assigned to communicate with an antenna array are monitored to determine if they are experiencing a decreased level of performance which may be caused by an overlapping back lobe from a neighboring cell site. If the user device's performance falls below a threshold value, the gain associated with the neighboring cell site is dynamically reduced in order to reduce the back lobe overlap.