Patent classifications
H04W24/02
METHOD AND SYSTEM FOR CLOUD EXTENDED ATTRIBUTE PROFILE
A method at a connector device, the method including receiving a first message from a peripheral device, the first message being received over a short range communications protocol connection utilizing a generic reading and writing service attribute profile; repackaging data within the first message into a second message at the connector device; and transmitting the second message to a network element, the transmitting utilizing a second communications connection, wherein the repackaging data populates a field within the second message with information about an attribute profile operation.
METHOD AND SYSTEM FOR CLOUD EXTENDED ATTRIBUTE PROFILE
A method at a connector device, the method including receiving a first message from a peripheral device, the first message being received over a short range communications protocol connection utilizing a generic reading and writing service attribute profile; repackaging data within the first message into a second message at the connector device; and transmitting the second message to a network element, the transmitting utilizing a second communications connection, wherein the repackaging data populates a field within the second message with information about an attribute profile operation.
CELLULAR NETWORK USER DEVICE MOBILITY OPTIMIZATION MANAGEMENT
Systems and methods to utilize user device self-reported quality metrics and machine learning mechanisms to optimize management of user device mobility in a cellular network. Cells in the network obtain quality data for one or more user devices in communication with the cells, including channel-quality-indicator values, reference-signal-received-power values, and reference-signal-received-quality values. The quality data is processed by a machine learning mechanism to generate a separate quality report for each cell. In response to receiving a request to handover communications for a target user device, the quality reports are utilized to select a cell that is predicted to provide the best quality communications for the target user device.
CONFIGURATION SYSTEM FOR A WIRELESS COMMUNICATION NETWORK
The application relates to a configuration system (100) for a wireless communication network (102) that comprises at least one first communication device (104b) and at least one second communication device (104c). The at least one first and second communication devices (104b, 104c) belong to a plurality of communication devices (104, 104a, 104b, 104c, 104d). Each communication device (104, 104a, 104b, 104c, 104d) in the plurality of the communication devices is a radio node device configured to provide a bi-directional radio communication with at least one of the plurality of the communication devices. After receiving (220) a content of a network persistent configuration data (CO) from a communication device (104a) belonging to the plurality of the communication devices and storing (222) the received content of the configuration data, each first communication device (104b) is configured to broadcast (224) a configuration data description (DE), which comprises a version identifier (VE) of the configuration data, periodically in the network for indicating a capability of said first communication device to send (228) the stored content of the configuration data, which is in accordance with the version identifier, on request.
CONFIGURATION SYSTEM FOR A WIRELESS COMMUNICATION NETWORK
The application relates to a configuration system (100) for a wireless communication network (102) that comprises at least one first communication device (104b) and at least one second communication device (104c). The at least one first and second communication devices (104b, 104c) belong to a plurality of communication devices (104, 104a, 104b, 104c, 104d). Each communication device (104, 104a, 104b, 104c, 104d) in the plurality of the communication devices is a radio node device configured to provide a bi-directional radio communication with at least one of the plurality of the communication devices. After receiving (220) a content of a network persistent configuration data (CO) from a communication device (104a) belonging to the plurality of the communication devices and storing (222) the received content of the configuration data, each first communication device (104b) is configured to broadcast (224) a configuration data description (DE), which comprises a version identifier (VE) of the configuration data, periodically in the network for indicating a capability of said first communication device to send (228) the stored content of the configuration data, which is in accordance with the version identifier, on request.
VEHICLE ROADSIDE UNIT INTERFERENCE DETECTION
An infrastructure device includes a transceiver, programmed to communicate with a plurality of vehicles, wherein at least one of the vehicles is located within a distance defined from a location of the infrastructure device, and at least one of the vehicles is located outside the distance from the location of the infrastructure device; and a controller, programmed to measure a channel busy ratio (CBR) for communication with the plurality of vehicles, measure a package error rate (PER) for communication with one or more of the vehicles located within the distance, and responsive to the CBR being greater than a CBR threshold, or the PER being greater than a PER threshold, record an interference event into a log.
USING PHYSICAL AND LOGICAL MODELING OF NETWORK INVENTORY RESOURCES FOR DISCOVERY, ASSIGNMENT AND ACTIVATION
The technologies described herein are generally directed to modeling network systems. For example, a method described herein can include receiving request data representative of a planning request for a network equipment project applicable to network equipment that is part of a network. Further, based on the request data and a logical inventory model of resources, the method can include identifying a logical process model for the network equipment project, corresponding to characteristics of service equipment applicable to the network equipment project. The method further includes transforming the logical process model into a physical process model that references the service equipment applicable to the network equipment project, and based on the request data and the physical process model, facilitating, for the network equipment project, the service equipment.
USING PHYSICAL AND LOGICAL MODELING OF NETWORK INVENTORY RESOURCES FOR DISCOVERY, ASSIGNMENT AND ACTIVATION
The technologies described herein are generally directed to modeling network systems. For example, a method described herein can include receiving request data representative of a planning request for a network equipment project applicable to network equipment that is part of a network. Further, based on the request data and a logical inventory model of resources, the method can include identifying a logical process model for the network equipment project, corresponding to characteristics of service equipment applicable to the network equipment project. The method further includes transforming the logical process model into a physical process model that references the service equipment applicable to the network equipment project, and based on the request data and the physical process model, facilitating, for the network equipment project, the service equipment.
VIRTUALIZED ARCHITECTURE FOR SYSTEM PARAMETER IDENTIFICATION AND NETWORK COMPONENT CONFIGURATION WITH REINFORCEMENT LEARNING
One or more computing devices, systems, and/or methods for system parameter identification and network component configuration are provided. A state comprising a system parameter combination, a traffic model, and a channel assignment may be generated. A network traffic scenario is executed through a virtualized testbed using the state. A reward for the system parameter combination may be generated based upon key performance indicators output by the network traffic scenario. A reward policy and rewards generated for system parameter combinations are used to select a system parameter combination that is used to configure a network component of a communication network.
VIRTUALIZED ARCHITECTURE FOR SYSTEM PARAMETER IDENTIFICATION AND NETWORK COMPONENT CONFIGURATION WITH REINFORCEMENT LEARNING
One or more computing devices, systems, and/or methods for system parameter identification and network component configuration are provided. A state comprising a system parameter combination, a traffic model, and a channel assignment may be generated. A network traffic scenario is executed through a virtualized testbed using the state. A reward for the system parameter combination may be generated based upon key performance indicators output by the network traffic scenario. A reward policy and rewards generated for system parameter combinations are used to select a system parameter combination that is used to configure a network component of a communication network.