A verification system implements technical solutions for verifying the delivery of messages transmitted by mobile communication systems and the processing of those messages. The message verification system includes a model database and verification processing circuitry configured to receive transmitter route data, receive receiver route data, determine a viewshed for a message, and compare the viewshed to the receiver route data.

Improving configuration of routing areas within an area of interest can include obtaining input data including a list of common language location identifiers within a defined area of interest and identification of a number of routing areas to be created within the area of interest; creating a bounding rectangle around the area of interest represented by the list of common language location identifiers; generating, within the bounding rectangle, a uniformly distributed sequence point; determining, from within the list of common language location identifiers, if the uniformly distributed sequence point is located in a particular common language location identifier of the list of common language location identifiers; if so, adding, to a list of kernel common language location identifiers the uniformly distributed sequence point; and if not, discarding the uniformly distributed sequence point.

Disclosed are systems and methods for a self-contained multi-modal communication system. The multi-modal communication system comprises a first mobile telecommunication node, which provides a private telecommunication network, a layer 2 (L2) backhaul wireless transceiver, an ethernet switch and an embedded edge cloud compute device. The edge cloud compute device includes an automatic failover detection system, wherein the automatic failover detection system receives as input a plurality of network parameters and automatically performs failover and communication modality switching for one or more communication devices associated with the self-contained multi-modal communication system.

The same or similar physical signals can be used for both user equipment (UE) and an integrate access backhaul (IAB) node. Different configurations of the resources and/or transmission periods of the signals can be used for initial access for access UEs and IAB nodes. In addition, to support topology formation, mobility/multi-connectivity procedures, and backhaul link management, periodic measurements and reports can be configured by a parent IAB node to a child IAB node UE function. This can comprise radio resource management (RRM), radio link monitoring (RLM), and beam management (L1-BM) measurements and reports.

A verification system implements technical solutions for verifying the delivery of messages transmitted by mobile communication systems and the processing of those messages. The message verification system includes a model database and verification processing circuitry configured to receive transmitter route data, receive receiver route data, determine a viewshed for a message, and compare the viewshed to the receiver route data.

Disclosed are systems and methods for a self-contained multi-modal communication system. The multi-modal communication system comprises a first mobile telecommunication node, which provides a private telecommunication network, a layer 2 (L2) backhaul wireless transceiver, an ethernet switch and an embedded edge cloud compute device. The edge cloud compute device includes an automatic failover detection system, wherein the automatic failover detection system receives as input a plurality of network parameters and automatically performs failover and communication modality switching for one or more communication devices associated with the self-contained multi-modal communication system.

A method performed by a first device is disclosed that includes sending a light of sight, LOS, determination request to a second device which communicates with the first device, wherein the LOS determination request includes an indication of a dual polarization procedure for Line of Sight (LOS), with the indication of the dual polarization procedure for LOS is used indicating that a same sequence of bits is sent at two polarizations to the same direction; a channel measurement for each of the two received sequences at the two polarizations is compared to determine whether a transmission between the first device and the second is LOS or NLOS.

Presented herein are systems and methods for detecting a boundary line crossing based on Round Trip Time (RTT) measured for wireless signals transmitted between and initiator wireless transceiver and a responder wireless transceiver deployed to form a straight boundary line. The initiator wireless transceiver transmits wireless probe signal(s) to the responder wireless transceiver, receives a wireless response signal transmitted by the responder wireless transceiver in response to the wireless probe signal(s), calculates an RTT combining a travel time of the wireless probe signal(s) and the travel time of the wireless response signal(s), compares the RTT to a reference RTT computed for a wireless probe signal and a corresponding wireless response signal transmitted in a clear straight transmission path while the boundary line is clear of obstacles and determines whether an object is blocking the straight transmission path based on a deviation of the RTT from the reference RTT.

The described technology is generally directed towards user equipment (UE) geolocation. A machine learning model can be trained to estimate UE locations based on historical network communication data associated with the UEs. In order to train the machine learning model, known previous UE locations and corresponding historical network communication data can be provided to the machine learning model. A variety of other information, such as topographical information, can also be provided to the machine learning model. The machine learning model can be trained to predict the known previous UE locations based on the corresponding historical network communication data and any other provided information. Once it is trained, the machine learning model can be deployed to estimate real-time UE locations based on historical network communication data associated with the UEs.

Presented herein are systems and methods for detecting a boundary line crossing based on Round Trip Time (RTT) measured for wireless signals transmitted between and initiator wireless transceiver and a responder wireless transceiver deployed to form a straight boundary line. The initiator wireless transceiver transmits wireless probe signal(s) to the responder wireless transceiver, receives a wireless response signal transmitted by the responder wireless transceiver in response to the wireless probe signal(s), calculates an RTT combining a travel time of the wireless probe signal(s) and the travel time of the wireless response signal(s), compares the RTT to a reference RTT computed for a wireless probe signal and a corresponding wireless response signal transmitted in a clear straight transmission path while the boundary line is clear of obstacles and determines whether an object is blocking the straight transmission path based on a deviation of the RTT from the reference RTT.