Device and method can be provided for emulating a system which includes a wireless channel, a wireless transmitter, and a wireless receiver. For example, with an emulation processor, it is possible to receive baseband data, process the received baseband data, and transmit the processed baseband data. Further, with a controller, it is possible to receive configuration information pertaining to the wireless channel, the wireless transmitter, and the wireless receiver to be emulated; and configure the emulation processor according to the received configuration information.

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.

A method for modeling a serializer/deserializer (SerDes) model includes generating plural data sets including noise simulation data of the SerDes model and output measurement data of an actual SerDes, training a machine learning model based on the plural data sets, and applying the trained machine learning model and an estimation model to a model included in the SerDes model. The estimation model provides the noise simulation data as an input to the trained machine learning model.

Concepts and technologies disclosed herein are directed to computer vision-based dynamic radio frequency (“RF”) planning and optimization. According to one aspect disclosed herein, a system can monitor cell site data from a cell site. The system can determine that the cell site data represents a change to the cell site. In response to determining that the cell site data represents the change to the cell site, the system can update clutter data associated with the cell site to reflect the change. The system can determine a potential RF signal attenuation associated with the object. The system can then determine that the potential RF signal attenuation associated with the object meets or exceeds a threshold. The system can trigger a remedial action to mitigate the potential RF signal attenuation.

The present disclosure relates to a 5th generation (5G) or pre-5G communication system for supporting a data transmission rate higher than that of a 4th generation (4G) communication system such as long term evolution (LTE). The present disclosure is to generate environment information for a network design, and a method for generating environment information may include determining a location difference value of a building between first information based on photographing and second information based on measurement, and correcting a location of an obstacle determined using the first information using the location difference value.

Path-loss measurements are determined for a test client device moving along a path in a field test environment in which field Wi-Fi mesh network nodes are distributed. The path-loss measurements are reproduced in a field-to-lab test environment that includes a test client device disposed in an electromagnetically-isolated chamber and field test Wi-Fi mesh network nodes disposed in respective electromagnetically-isolated chambers. The test client device and the field test Wi-Fi mesh network nodes are in wired or wireless communication with each other via signal lines. A programmable attenuator is electrically coupled to each signal line. The attenuation of each programmable attenuator is varied to reproduce the path-loss measurements from the field test environment. Path-loss measurements at the location of each field Wi-Fi mesh network node are also reproduced with the programmable attenuators to reproduce the field Wi-Fi mesh network node configuration.

Methods, apparatuses, systems, and non-transitory computer-readable medium are disclosed relating to abnormal transmission identification. One method comprises, at a receiving device, receiving a V2X message from a transmitting device. The method further comprises determining a signal propagation context for the receiving device and obtaining an RSSI value and a distance value for the V2X message. The method further comprises generating an adjusted RSSI value based on (1) the RSSI value and (2) the signal propagation context for the receiving device. The method further comprises obtaining a predetermined RSSI-to-distance relationship model and comparing an adjusted RSSI-to-distance data pair, comprising the adjusted RSSI value and the distance value, to the predetermined RSSI-to-distance relationship model. The method further comprises, in response to determining that the adjusted RSSI-to-distance data pair fails a criterion for conforming to the predetermined RSSI-to-distance relationship model, identifying the V2X message as an abnormal transmission.

Various embodiments may provide systems and methods for managing transmit (TX) timing of data transmissions. The methods include applying a plurality of radio frequency (RF) channel factors related to data uplink transmissions by the wireless device to a TX timing model configured to provide as an output a TX timing for a data transmission to a base station and a number of carriers for sending the data transmission, and selecting a TX time and a number of carriers for sending a next data transmission to the base station based in part on the TX timing model output.

The technologies described herein are generally directed to facilitate allocating resources to zones for IOT equipment in a fifth generation (5G) network or other next generation networks. An example method discussed herein includes identifying, by carrier allocation equipment, carrier transmission information corresponding to transmission of a first carrier signal configured to support Internet of things equipment. The method can further comprise analyzing, by the carrier allocation equipment, the carrier transmission information to determine coverage information corresponding to a potential for coverage, by the first carrier signal, of an Internet of things equipment support zone corresponding to a geographic area. The method can further include, based on the coverage information, facilitating configuring transmission parameter information, representative of a transmission parameter applicable to the coverage of the Internet of things equipment support zone by the first carrier signal.

The disclosed system for testing a massive MIMO beamforming antenna array of arbitrary size includes an anechoic chamber, and a mount for a MIMO array antenna positioned in the chamber, wherein the array has at least 8×4 antenna elements that are individually activated to steer transmissions from the array. The system includes dual element antenna probes positionable in the anechoic chamber, with feeds coupling one or more UE sources to the antenna probes; and the UE sources generate RF in OTA communication with the array, emulating multiple UE devices. Additionally the system includes base station electronics coupled to the array, and a test controller coupled to the base station electronics. The test controller signals the UE sources OTA via the array to invoke a connection to the UE sources and measure OTA channel performance between the array and the multiple UE devices emulated, the performance including at least throughput.