T-mobile Innovations LLC

T-mobile Usa, Inc.

Oliver Philippe Coudert

Bharatwajan Raman

Lyle W Paczkowski

Durga P Satapathy

Pei Hou

Walter Fred Rausch

Nirmal Chandrasekaran

Alfred Richard Balakier

Usama Masood

Junaid Alam

Mark Holland

Ronald Richard Marquardt

Systems, methods, and computer-readable media are described herein which utilizes and controls an electromagnetic energy beam steering apparatus. The electromagnetic energy beam steering apparatus uses directional properties of a Luneburg lens to receive RF energy from one or more points of the Luneburg lens and re-transmits the RF energy from a different point of the Luneburg lens to focus the RF energy in a desired direction. The electromagnetic energy beam steering apparatus may take a form of a passive repeater, an active repeater, or a multipath active repeater.

Luneburg lens signal repeater

Systems and methods for immutable archiving of UE connection data for wireless communications networks are provided. In one embodiment, a method comprises: detecting when a UE has initiated access to a network operator core through a radio access network; determining whether a witness data collection service is to be activated for the UE; when the witness data collection service is to be activated: activating the wireless data collection service for a UE monitoring session; initiating transmission of a UE monitoring session block sequence from the UE to the network operator core, wherein the session block sequence comprises blocks each comprising collected witness data characterizing a connection between the UE and the network operator core during the UE monitoring session; determining when the UE monitoring session is complete; closing the session block sequence to form a ledger archive and storing the ledger archive to an immutable witness data archive.

Systems and methods for immutable archiving of user equipment connection data for wireless communications networks

A wireless communication device is disclosed that includes a non-transitory memory, a processor, and a local agent. The local agent transmits context information to an AI engine and receives and stores sign language data sets selected based on the context information from the AI engine in the non-transitory memory. The local agent receives content in need of language assistance. In response to a determination to process the content locally, the local agent converts the content into first sign language gestures based on the data sets. In response to a determination to process the content remotely, the local agent sends at least some of the content to the AI engine, receives keys from the AI engine, and determines second sign language gestures based on the keys and the data sets. The local agent sends the first or second sign language gestures to a display of the wireless communication device for presentation.

Delivery of artificial intelligence based context-sensitive language assistance to wireless communication devices

A wireless communication network attests to a geographic location of a wireless user device. An access node receives signaling transferred by the wireless user device that indicates the wireless user device, the geographic location, satellite signal characteristics for the geographic location, and terrestrial signal characteristics for the geographic location. The network access node transfers the signaling to a location attestation node. The location attestation node determines known signal characteristics for the geographic location. The location attestation node compares the known signal characteristics to the satellite signal characteristics and the terrestrial signal characteristics. The location attestation node generates a location-attestation score based on the comparison. The location attestation node transfers information that indicates the wireless user device, the geographic location, and the location-attestation score. The location attestation node may comprise a distributed ledge node.

User geographic location attestation by a wireless communication system

A wireless communication system attests to user data from a wireless user device. The wireless user device receives satellite signals from satellites and determines satellite signal metrics for the satellite signals. The wireless user device determines its geographic location based on the satellite signals. The wireless user device executes an operating system in trusted processing circuitry in response to device power-up. The wireless user device executes a network application in the trusted processing circuitry. The network application transfers the user data, geographic location, and signal metrics to network elements. The network elements determine known satellite metrics for the geographic location. The network elements compare the satellite signal metrics to the known satellite metrics and generate an attestation score for the user data based on the satellite comparison. The network elements store the user data, the geographic location, and the attestation score. The network elements may comprise distributed ledger nodes.

Data attestation in a wireless communication system

System and method are provided to incorporate radar technology in a time-division duplex radio access network. Information in the guard period between the downlink transmission and uplink transmission, such as the capturing of the UL RF signal landscape, is modified to capture radar signals (RF signals) that reflect from objects. The reflected radar signals are stored, process, and analyzed by a connected computer to determine stationary and moving objects.

Incorporating radar technology in a time-division duplex radio access network

The system obtains KPIs of a cell of a telecommunication network. The system preprocesses the multiple KPIs by reducing noise of the multiple KPIs and normalizing an amplitude of a KPI among the multiple KPIs. The system identifies a performance issue of the network by executing multiple ML models based on the KPIs, where a first ML model is configured to identify a sudden performance degradation, where a second ML model is configured to identify an event leading to a change in a performance trend, where a third ML model is configured to identify a gradual change in the performance trend, and where a fourth ML model is configured to identify whether the cell of the network is nearing a capacity limitation of the cell. The system provides a report based on the identified performance issue.

Identifying a performance issue associated with a 5G wireless telecommunication network

A wireless communication system wirelessly transfers a network integration request to a distributed ledger over a communication satellite. The network integration request indicates an access node identifier, ledger credentials, and geographic location. The distributed ledger validates the ledger credentials, and in response, translates the access node identifier and the geographic location into an access node configuration. The distributed ledger transfers the access node configuration to the wireless access node over the communication satellite. Based on the access node configuration, the wireless access node wirelessly registers with a wireless communication network, wirelessly exchanges user data between User Equipment (UEs) and the wireless communication network, and hands-over some of the UEs with neighbor access nodes.

Growing community of inventors

Arlington, VA, United States of America

Oliver Philippe Coudert