The computer-implemented method includes simulating, by a processor, using an electromagnetic solver including ray launching or ray tracing, multiple rays that reach a vicinity of a receiver of a wireless channel, determining locations of interactions of the rays with an environment of the wireless channel, post-processing, using one or more of the multiple rays, information about received signal at the receiver to obtain temporal variations therein, and determining a characteristic of the wireless channel using results of the post-processing.

The present development details a method and apparatus for performing channel emulation of doubly selective scenarios, where the simulation and emulation duration is arbitrarily long for a stationary or non-stationary channel, with non-separable dispersion which is achieved by combining the techniques of channel orthogonalization, decomposition of the correlation tensor in the Doppler domain into frequency-dependent correlation matrices, followed by a matrix factorization of each of the mentioned matrices and, finally, the use of the windowing method to generate arbitrarily long achievements which thereby allows the concatenation of channel realizations coming from the same or different NSSF, thus achieving reproduction of stationary or non-stationary channels, respectively.

A first mobile terminal testing device 1 including plurality of pseudo base station units 12-0, 12-1 operating as LTE base stations of NSA, and second mobile terminal testing device 2 operating as 5G NR base stations of NSA are provided. Each of the pseudo base station units 12-0, 12-1 is associated with the second mobile terminal testing devices 2, 2. The second mobile terminal testing device 2 generates a 5G NR control signal when testing a mobile terminal 3 which supports for NSA. The generated 5G NR control signal is transmitted to the first mobile terminal testing device 1. The first mobile terminal testing device 1 transmits the received 5G NR control signal to the mobile terminal 3 by the LTE control signal using the pseudo base station unit 12 corresponding to the second mobile terminal testing device 2 which transmits the control signal.

A method for radar full blockage detection includes transmitting, via a transceiver, radar signals for object detection. The method also includes determining whether an object is detected within a first threshold distance based on reflections of the radar signals that are received. In response to a determination that the object is detected within the first threshold distance, the method includes determining whether the object is detected beyond a second threshold distance, based on the reflections of the radar signals. The second threshold distance is further away from the electronic device than the first threshold distance. In response to determining that the object is within the first threshold distance and not detected beyond the second threshold distance, the method includes determining that the transceiver is fully blocked by the object. upon a determination that the transceiver is fully blocked, the method includes modifying a wireless communication operation associated with the transceiver.

The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. A communication environment analysis method according to the present invention comprises the steps of: receiving satellite information and image information of a certain area; identifying area information of an object that is not contained in the image information, on the basis of the satellite information; determining characteristic information of the object; and analyzing a communication environment of the certain area on the basis of the characteristic information, wherein the object is one that causes signal attenuation due to at least one of signal scattering and signal absorption.

A system for load-testing a cloud radio access network (C-RAN) is provided. The system includes at least one radio point (RP), each being configured to exchange radio frequency (RF) signals with at least one user equipment (UE). The system also includes a baseband controller communicatively coupled to the at least one RP via a front-haul ETHERNET network. The front-haul ETHERNET network includes at least one switch; and a testing device that is time-synchronized to the baseband controller and the at least one RP. The testing device is configured to receive at least one packet from each of the at least one RP. The testing device is also configured to replicate each of at least some of the received packets to produce a respective replicated packet. The testing device is also configured to transmit at least one replicated packet to the baseband controller.

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.

Methods and systems for detecting an enhanced massive mobile broadband (eMBB) physical downlink control channel (PDCCH) in the presence of for ultra-reliable low latency communication (URLLC) users are disclosed. A eMBB wireless transmit/receive unit (WTRU) may receive a eMBB control resource set (CORESET) configuration for a CORESET including a PDCCH preemption indicator. If PDCCH preemption is enabled based on the PDCCH preemption indicator, the eMBB WTRU may identify and remove preempted resource element groups (REGs) in the eMBB CORESET by comparing channel estimates for each REG bundle in the eMBB CORESET. The WTRU may perform channel estimation based on remaining REGs in the eMBB CORESET and detect the PDCCH by performing blind decoding, based on a received signal, on the remaining REGs in the eMBB CORESET.

Implementations relate to selection of a physics-specific model for determination of characteristics of radio frequency signal propagation. In some implementations, a method includes receiving a plurality of first propagation characteristics of a radio frequency (RF) signal, determining a feature vector based on the first propagation characteristics, inputting the feature vector to a machine-learning meta-model, and executing the machine learning meta-model to select a particular physics-specific model from multiple physics-specific models, where each of the physics-specific models is for a different RF signal propagation environment. The feature vector is input to the particular physics-specific model, and the particular physics-specific model is executed to output an estimate of one or more second propagation characteristics of the RF signal based on the feature vector.

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.