A radio terminal accommodation determination device includes: an average received power calculation unit for calculating an average received power for each mesh constituting an area; an interfering signal power CDF creation unit for creating a cumulative distribution function of all interfering signal powers; an intended signal power PDF creation unit for creating a fourth probability density function indicating a probability density function of an intended signal power; and a communication success rate estimation unit for calculating, for each base station, a communication success rate of the intended terminal based on the cumulative distribution function and the fourth probability density function.

Examples disclosed herein relate to a sensor fusion scanning system for wireless network planning. The system includes a sensor scanning mobile platform comprising a beam steering radar sensor and one or more auxiliary sensors, the sensor scanning mobile platform configured to scan a wireless environment, a reflectivity engine configured to generate a reflectivity representation of the wireless environment based on radar data from the beam steering radar sensor, a sensor fusion processing engine configured to generate a Three-Dimensional (“3D”) representation of the wireless environment based on the radar data and sensor data from the one or more auxiliary sensors, and a reflectarray planning engine configured to design a plurality of reflectarrays and determine locations for the plurality of reflectarrays in the wireless environment based on the reflectivity representation and the 3D representation.

Systems, methods, and other embodiments associated with eviction of weakly correlated signals from collections are described. In one embodiment, a mock signal that has random signal properties is generated. A mock correlation coefficient between the mock signal and a measured time series signal from a collection of measured time series signals is then generated. A discrimination value that indicates a weak signal correlation is then selected, based at least in part on the mock correlation coefficient. A first measured signal is then identified from the collection of measured time series signals that has the weak signal correlation by determining that a first correlation coefficient between the first measured signal and a second measured signal is weak based on the discrimination value. The first measured signal is then evicted from the collection of signals in response to the determination that the first measured signal has the weak signal correlation.

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.

A system for emulating a plurality of wireless communication channels is provided. The system includes a plurality of elevation steering devices configured to modify at least one elevation characteristic of a plurality of signals and a plurality of combiners. Each combiner is configured to combine at least two signals of the plurality of signals to output a combined signal. The plurality of combiners output a plurality of combined signals. The system includes a plurality of azimuth steering devices configured to modify at least one azimuth characteristic of the plurality of combined signals. The plurality of elevation steering devices and the plurality of azimuth steering devices emulate the plurality of wireless communication channels.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for processing communications signals using a machine-learning network are disclosed. In some implementations, pilot and data information are generated for a data signal. The data signal is generated using a modulator for orthogonal frequency-division multiplexing (OFDM) systems. The data signal is transmitted through a communications channel to obtain modified pilot and data information. The modified pilot and data information are processed using a machine-learning network. A prediction corresponding to the data signal transmitted through the communications channel is obtained from the machine-learning network. The prediction is compared to a set of ground truths and updates, based on a corresponding error term, are applied to the machine-learning network.

A method is provided for generating test data for testing radio equipment. The method includes: determining, by a test apparatus, one or more beam identifiers; selecting, by the test apparatus, based on the one or more beam identifiers, one or more radio channel models; receiving, by the test apparatus, a baseband signal representing I/Q data of one or more beamforming antennas; processing, by the test apparatus, the baseband signal representing I/Q data according to the selected radio channel model; and transmitting, by the test apparatus, the processed baseband signal representing I/Q data to a radio equipment under test.

An electronic device that assesses communication performance is described. During operation, the electronic device receives information specifying a location in an environment. For example, the information may correspond to user-interface activity associated with a user interface. Notably, the user interface may include an augmented reality and the user-interface activity may include defining the location, such as by dropping a pin in the augmented reality. Then, the electronic device provides the information to an access point and/or a controller of the access point, where the location is within communication range of the access point. Next, the electronic device receives, from the access point and/or the controller, measurements of one or more communication performance metrics at or proximate to the location during a time interval. Moreover, the electronic device provides a graphical representation of the communication performance at or proximate to the location based at least in part on the measurements.

An interference detection system in a network identifies a first wireless station that has experienced radio frequency (RF) interference from an unknown source on at least one physical resource block (PRB) by determining that a key performance indicator (KPI) for the at least one PRB on the first wireless station has a value indicative of interference. The interference detection system identifies one or more second wireless stations that have experienced similar interference on the at least one PRB. A plurality of estimated interference source locations are determined based at least on geographic locations of the first wireless station and the one or more second wireless stations. Determining the plurality of estimated interference source locations further comprises generating a boundary based on the geographic locations of the first wireless station and the one or more second wireless stations and selecting a plurality of estimated interference source locations within the boundary.

Some embodiments of this disclosure are directed to apparatuses and method for establishing signal-to-noise ratio (SNR), useful signal power level (Es) and artificial noise power level (Noc) values for new radio (NR) performance requirements. The apparatuses and methods can include processing a received signal including the Es and Noc and determining a baseband signal-to-noise ratio (SNR) degradation based on the signal power level, the artificial noise power level, and the radio-frequency noise power level. The apparatuses and methods can then determine a compensated SNR degradation, as a performance requirement, based on the baseband SNR degradation and the radio-frequency noise power level.