The present disclosure relates to a method for operating a terminal and a base station in a wireless communication system and an apparatus for supporting the same. In an embodiment of the present disclosure, a method for operating a terminal in a wireless communication system may include: transmitting a first message including information related to learning; receiving a second message including configuration information for learning; transmitting an uplink reference signal; and transmitting channel information related to a downlink channel measured based on a downlink reference signal.

One or more systems and methods for wireless equipment deployment are provided herein. Imagery of locations depicting structures within a list of structures is analyzed to identify features of the structures within the locations. Ranks may be calculated for the structures based upon structure scores and installation scores calculated from the features. In response to a rank for a structure exceeding a threshold, wireless equipment deployment of a communication device may be triggered so that the communication device is controlled to exchange communication signals with devices proximate the structure.

An example of an object of the present disclosure is to provide an interference detection apparatus, an interference detection method, and a non-transitory computer-readable medium that allow a user to determine a priority of interference to be dealt with in communication. The interference detection apparatus according to an example embodiment includes at least one memory configured to store an instruction, and at least one processor configured to execute the instruction. The processor is further configured to learn a signal state model by using a learning signal in a communication signal, acquire a detection target signal in the communication signal, detect interference in the detection target signal, and calculate a severity of interference in the detection target signal by using the detection target signal, a detection result of the interference, and the learned signal state model.

A test and measurement system includes a machine learning system, a test and measurement device including a port configured to connect the test and measurement device to a device under test (DUT), and one or more processors, configured to execute code that causes the one or more processors to: acquire a waveform from the device under test (DUT),transform the waveform into a composite waveform image, and send the composite waveform image to the machine learning system to obtain a bit error ratio (BER) value for the DUT. A method of determining a bit error ratio for a device under test (DUT), includes acquiring one or more waveforms from the DUT, transforming the one or more waveforms into a composite waveform image, and sending the composite waveform image to a machine learning system to obtain a bit error ratio (BER) value for the DUT.

A processor-implemented method is presented. The method includes receiving an input sequence comprising a group of channel dynamics observations for a wireless communication channel. Each channel dynamics observation may correspond to a timing of a group of timings. The method also includes determining, via a recurrent neural network (RNN), a residual at each of the group of timings based on the group of channel dynamics observations. The method further includes updating Kalman filter (KF) parameters based on the residual and estimating, via the KF, a channel state based on the updated KF parameters.

Aspects of the subject disclosure may include, for example, network deployment or radio-propagation computation based on a combination of photon mapping and machine learning including supporting near-real-time computation of the radio transmissions for different layouts of antennas and allowing examination of a large variety of antenna locations and layouts, changing configuration details, e.g., tilting antennas or optimally selecting the sector that each antenna covers, and so on. Other embodiments are disclosed.

This disclosure proposes a system to manage radio frequency (RF) interferences towards earth stations to solve needs of network providers. For example, user a user equipment that is close to an earth station can cause signal interference with the earth station as the user equipment is communicating with a base station. However, if the base station shares earth station location information with the user equipment, the user equipment can adjust its frequency and/or reduce its signal power to mitigate interference with the earth station. Alternatively, or in addition to, the base station can adjust its signal strength, and/or terminate a signal or resource that it is sending to the user equipment to prevent signal interference with the earth station.

A method, apparatus, and computer-readable medium are provided that performs an interference measurement with an enhanced accuracy. The apparatus detects a signal from a serving cell, a neighbor cell, or a second apparatus in the neighbor cell. The apparatus estimates at least one of a downlink-downlink interference and a cross-uplink-downlink interference of the neighbor cell or the second apparatus in the neighbor cell. In another aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided that configures a User Equipment (UE) to perform the interference measurement and receives an interference measurement report from the UE. The apparatus estimates at least one of an uplink-uplink interference and a cross-downlink-uplink interference of the neighbor cell or the second apparatus in the neighbor cell.

Aspects of the subject disclosure may include, for example, a machine-readable medium with executable instructions that facilitate performance of operations by a processor including receiving a registration for a trajectory of a satellite; estimating a zone of occupancy at a future time for the satellite; determining an interference of the satellite from the zone of occupancy at the future time; determining a deconfliction for minimizing or eliminating the interference; and sending the deconfliction to a controller of the satellite. Other embodiments are disclosed.

Discussed herein are devices, systems, and methods for decentralized device management. A method can include receiving a first message from a second device, implementing a first machine learning (ML) model that operates on the received first message and an observation to determine a next objective to be completed by the first device, and training a simulator to produce the first message based on the observation.