Devices and methods enable optimizing a signal of interest based on identifying and analyzing the signal of interest based on radio frequency energy measurements. Signal data is compared with stored data to identify the signal of interest. Signal degradation data is calculated based on noise figure parameters, hardware parameters and environment parameters. The signal of interest is optimized based on the signal degradation data. Terrain data is also operable to be used for optimizing the signal of interest.

Disclosed are a communication method, a secondary network node, and a terminal. The method includes a secondary network node acquires a network state of a cell served by the secondary network node; the secondary network node updates a network configuration of the cell served by the secondary network node according to the network state of the cell served by the secondary network node; the secondary network node sends first update configuration information to a terminal, wherein the first update configuration information is used for updating the network configuration of the cell served by the secondary network node. The network configuration of the cell served by the secondary network node is autonomously updated by the secondary network node according to the network state of the cell served by the secondary network node.

A communication system facilities low-latency, high-availability multipath streaming between terminals (e.g., mobile terminals) and a server platform. In an example application, a remote support service operating on the server platform provides remote teleoperation, monitoring, or data processing services to a mobile terminal embodied as a vehicle or robot utilizing a low latency communication link. The low latency link enables a remote operator to receive video or telemetry feeds, and timely monitor and respond to hazards in substantially real-time. The low latency communication link may be achieved even when the data streams are transmitted over public networks incorporating at least one wireless leg, and where individual connections have varying quality of service in terms of delivery latency due to congestion or stochastic packet losses. Assignment of data streams to particular communication channels may be made on an optimization model derived from a machine-learning process or simulation.

Techniques are described in which a network management system (NMS) is configured to determine a root cause of degraded network performance based on SLE metrics and the locations associated with network devices providing the SLE metrics. The NMS can determine service level experience (SLE) metrics associated with each client device on a network and location data for each client device of the plurality of client devices. The NMS can generate a time series of parameter vectors, where each parameter vector includes SLE metrics corresponding to each client device of the plurality of client devices. Each parameter vector is associated with the location of the client device corresponding to the SLE metrics. The NMS can determine, based on the time series of parameter vectors and associated locations, a root cause for a degradation in SLE metrics associated with the one or more of the client devices.

Systems, apparatuses and methods may provide for technology that adjusts, via a short-term subsystem, a communications parameter for one or more of wireless communication devices based on data from one or more of a plurality of sensors. The technology may also determine, via a neural network, a prediction of future performance of the wireless network based on a state of the network environment, wherein the state of the network environment includes information from the short-term subsystem and location information about the wireless communication devices and other objects in the environment, and determine a change in network configuration to improve a quality of communications in the wireless network based on the prediction of future performance of the wireless network. The technology may further generate generic path loss models based on time-stamped RSSI maps and record a sequence of events that cause a significant drop in RSSI to determine a change in network configuration.

A network device determines radio frequency (RF) conditions at a first endpoint and a second endpoint of a call or session. The network device determines optimum first codec parameters for the determined RF conditions at the first endpoint of the call or session, and determines optimum second codec parameters for the determined RF conditions at the second endpoint of the call or session. The network device sends the first codec parameters to the first endpoint for altering operation of a first codec at a first device at the first endpoint. The network device sends the second codec parameters to the second endpoint for altering operation of a second codec at a second device at the second endpoint.

A method, device, and non-transitory computer-readable medium provide for scanning, by a device, a radio service area of a small cell radio access node to detect radio signals of one or more radio frequency (RF) bands, the radio signals including transmissions associated with one or more other small cell radio access nodes that are operating in a vicinity of the small cell radio access node, and the small radio access node being configured to alternately operate at multiple RF bands including the one or more RF bands; determining, by the device, a signal strength associated with each of the one or more RF bands; and dynamically optimizing, by device, operation of the small cell radio access node based on the signal strength associated with each of the one or more RF bands.

The described technology is generally directed towards reducing latency in a wireless communications network. Radio access network latency data corresponding to a measured latency impact criterion is obtained by a network device of a wireless network. Based on the radio access network latency data, latency guidance data usable by the radio network device to achieve a reduction in communication latency that is experienced by a user equipment is predicted, e.g., by a learned model. The latency guidance data can be used to facilitate a reduction in the communication latency that is experienced by a user equipment.

A method performed by a User Equipment (UE) for managing sub-flow communications is provided, the method includes selecting a sub-flow among a plurality of sub-flows of the UE based on a set of parameters associated with each of the plurality of sub-flows, and transmitting a plurality of Transmission Control Protocol (TCP) acknowledgement messages in a single frame through the selected sub-flow, the plurality of TCP acknowledgement messages being associated with the plurality of sub-flows.

A wireless communication device that transmits data to another wireless communication device that performs wireless connection using a packet including a transmission number, the wireless communication device includes, a controller configured to classify the data as first data when a transmission condition indicating a condition related to transmission of the data is a first transmission condition and classifies the data as second data when the transmission condition of the data is a second transmission condition different from the first transmission condition, and a transmitter configured to transmit the data in a first transmission mode in a layer related to the wireless connection when the data is the first data and transmits the data in a second transmission mode in a layer related to the wireless connection when the second data is second data.