Abstract: Methods, systems, and devices for wireless communications are described. A network entity may transmit a set of spatially multiplexed synchronization signals in a same symbol period. The set of spatially multiplexed synchronization signals may indicate a parameter, such as a cell identifier, for the network entity. The network entity may select a sequence for each synchronization signal of the set. A user equipment (UE) may monitor for the set of spatially multiplexed synchronization signals during the same symbol period. The UE may differentiate each synchronization signal based on a respective sequence used to transmit each synchronization signal. The UE may determine that the set of spatially multiplexed synchronization signals were transmitted by the network entity using multiple antenna ports. The UE may determine the parameter for the network entity based on receiving the set of spatially multiplexed synchronization signals.

Abstract: Methods, systems, and devices for wireless communications are described. In some wireless communications systems, a user equipment (UE) and a network entity may utilize multi-port mobility reference signals to assist with spatial based mobility procedures. The UE may receive a reference signal that is associated with multiple antenna ports. The UE may measure a multi-dimensional channel response based on the reference signal. The multi-dimensional channel response may be associated with measured channel metrics corresponding to the multiple antenna ports. The UE may transmit a report that includes a channel measurement vector based on the multi-dimensional channel response. The channel measurement vector may indicate multiple measured channel metrics for one or more dimensions of the multi-dimensional channel response. The network entity may transmit a message that indicates one or more metrics associated with mobility management for the UE based on the report that indicates the channel measurement vector.

Abstract: A method, for detecting a position change of a lane marker, includes: determining, based on a first measurement data of a distance between the lane marker and a reference marker on a road that is obtained from a first road data collected via a high-precision device at a first time point, a first set of changed regions between the lane marker and the reference marker in which the distance has changed; determining a second set of changed regions between the lane marker and the reference marker in which the distance has changed based on a second measurement data of the distance that is obtained from a second road data collected via a low-precision device at a second time point after the first time point; and detecting the position change of the lane marker between the first time point and the second time point.

Abstract: Existing program code, which is executable on one or more computers forming part of a distributed computer system, is analyzed. The analysis identifies log output instructions present in the program code. Log output instructions are those statements or other code that generate log messages related to service requests processed by the program code. A log model is generated using the analysis. The log model is representative of causal relationships among service requests defined by the program code. The log model can then be applied to logs containing log messages generated by execution of the program code, during its normal operation, to group log messages for improved analysis, including visualization, of the performance and behaviour of the distributed computer system.

Abstract: Existing program code, which is executable on one or more computers forming part of a distributed computer system, is analyzed. The analysis identifies log output instructions present in the program code. Log output instructions are those statements or other code that generate log messages related to service requests processed by the program code. A log model is generated using the analysis. The log model is representative of causal relationships among service requests defined by the program code. The log model can then be applied to logs containing log messages generated by execution of the program code, during its normal operation, to group log messages for improved analysis, including visualization, of the performance and behaviour of the distributed computer system.

Abstract: Existing program code, which is executable on one or more computers forming part of a distributed computer system, is analyzed. The analysis identifies log output instructions present in the program code. Log output instructions are those statements or other code that generate log messages related to service requests processed by the program code. A log model is generated using the analysis. The log model is representative of causal relationships among service requests defined by the program code. The log model can then be applied to logs containing log messages generated by execution of the program code, during its normal operation, to group log messages for improved analysis, including visualization, of the performance and behavior of the distributed computer system.

Abstract: Existing program code, which is executable on one or more computers forming part of a distributed computer system, is analyzed. The analysis identifies log output instructions present in the program code. Log output instructions are those statements or other code that generate log messages related to service requests processed by the program code. A log model is generated using the analysis. The log model is representative of causal relationships among service requests defined by the program code. The log model can then be applied to logs containing log messages generated by execution of the program code, during its normal operation, to group log messages for improved analysis, including visualization, of the performance and behaviour of the distributed computer system.