At&t Mobility Ii LLC

At&t Intellectual Property I, L.p.

At&t Technical Services Company, Inc.

At&t Mobiliiy Ii LLC

Kurt Donald Huber

Judson Flynn

William Gordon Mansfield

Arthur Richard Brisebois

Thomas W Henderson

Cheng P Liu

Alireza Farid Faryar

Jeffrey Mikan

Julius Fodje

Jefferey Thomas Seymour

Robert Wayne Lott

Mark D Austin

Yung Shirley Choi-Grogan

Spyridon Kapoulas

Daniel Vivanco

John Potts Davis, Iii

Ravindra Babu Gurajala

Sheldon Kent Meredith

Sangar Dowlatkhah

Robert C Streijl

Patrick Shane Morrison

Henry Jackson Fowler, Jr

Hristo Hristov

Jerome Hetrick

Yupeng Jia

Hongyan Lei

Sarat Puthenpura

Zihui Ge

Yonghui Tong

Rick Tipton

Brian Keith Rainer

Ajay Mahimkar

David Lee Applegate

David R Glass

Shomik Pathak

Michael A Salmon

Glen Zdroik

Liane F Rulifson

Thomas Joseph Pitassi

Swati Roy

Daniel C Edwards

Ewa Monika Reppling Sack

Robert Bryon Chambers

Daniela Pechova Diefenbach

Gerald V Porter

William Adams

Victoria Collier

Dipak Kumar Sahoo

Stephen Leon Favor

Alfreda Downie

Rahul Neelakantan

Ramzi Barghouthi

Robert Taylor

Dan Edwards

Paul Turner

Judson John Flynn

The technologies described herein are generally directed to mapping signal propagation using idle mode user equipment in a fifth generation (5G) network or other next generation networks. An example method can include, facilitating receiving, a message from a user equipment, with the message including signal information describing detection of a signal of a carrier of base station equipment while the user equipment was in an idle mode at a first location. The method can further include identifying a second location of the base station equipment corresponding to a time when the signal was transmitted, wherein the second location is different from the first location. Further, the method can include based on the first location, the second location, and the signal information, estimating a path loss of the carrier at the first location.

Estimating signal propagation based on sampling by user equipment in idle mode

The technologies described herein are generally directed to generating a propagation model based on sampling by user equipment in idle mode in a fifth generation (5G) network or other next generation networks. An example method can include, based on a first location in a geographic area of a signal measurement measured by a user equipment in an idle mode, and a transmission location of the signal, estimating an estimated first path loss value. The method can further include, based on the estimated first path loss value and a second path loss value of a second carrier signal received from the carrier signal source, determining an antenna pattern of the carrier signal source. Further, the method can include based on the antenna pattern, generating a propagation model for the carrier signal source.

Generating a propagation model based on sampling by user equipment in idle mode

The technologies described herein are generally directed to providing radio resources to facilitate a predicted transition to active mode by idle user equipment in a fifth generation (5G) network or other next generation networks. An example method can include predicting that a user equipment of a group of user equipment in an idle mode will transition to an active mode during a time duration. The method can further include, identifying base station equipment that are able to provide coverage to the group of user equipment during the time duration. Further, the method can include, based on predicting the user equipment will transition to active mode, prioritizing allocation among the base station equipment, of resources to provide coverage to facilitate an active mode connection by the user equipment to the base station equipment.

Allocating resources among communication cells based on a potential communication load of user equipment in idle mode

The technologies described herein are generally directed to providing, based on a paging message, radio resources to facilitate a transition to active mode by idle user equipment in a fifth generation (5G) network or other next generation networks. An example method can include identifying an idle mode activation message. The method can further include, based on the activation message, predicting that the user device is going to request an active connection. Further, the method can include prioritizing allocation of antenna resources to the user device over different user devices in an idle state, based on a prediction that the user device will transition to an active state before the different user devices. Further, the method can include, based on the prioritizing, directing a base station to cause a beamformed signal to a predicted location of the user device to accept the active connection.

Facilitating transition to active mode by an idle device based on an activation request

The technologies described herein are generally directed to providing radio resources to facilitate a predicted transition to active mode by idle user equipment in a fifth generation (5G) network or other next generation networks. An example method can include predicting that a user equipment of a group of user equipment in an idle mode will transition to an active mode after passage of a time duration, starting from the predicting, that is lower than a time threshold. The method can further include identifying base station equipment that is able to provide coverage to the user equipment during the passage of the time duration before the user equipment transitions to the active mode. Further, the method can include prioritizing allocation of, within the group of user equipment, an antenna resource of the base station equipment to provide the coverage to facilitate an active mode connection by the user equipment to the base station equipment.

Allocating radio resources to idle user equipment that was predicted to transition to active mode

The technologies described herein are generally directed to preparing for a connection with a user equipment while the user equipment is in an idle state in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include facilitating transmitting a signal directed by an antenna of base station equipment. The method can further include, facilitating receiving, from a user equipment, a message, wherein the message comprises feedback information describing receipt of the signal while the user equipment was in an idle mode at a location. Further, the method can comprise, based on the feedback information and the location, generating a model of signal propagation applicable to signals at the location.

Allocating antenna resources to prepare for idle equipment to transition to active mode

Network planning based on collected crowd-sourced access point quality and selection data can optimize access point frequency and/or bandwidth selection. A cloud-based application can be utilized in conjunction with a mobile device to build a database of access point quality and thresholds suitable for real-time and other jitter-sensitive services. The mobile device jitter measurements and selection thresholds can be collected at a cloud platform, which creates an access point performance and selection threshold profile from which the network can facilitate access point frequency and/or bandwidth selections.

Network planning based on crowd-sourced access point data for 5G or other next generation network

When frequency range 1 (FR1) (e.g., Sub6 Ghz radio coverage), and FR2 (e.g., mmW coverage) are present in a given area, there can be a broader coverage from FR1 broadcasting in addition to targeted coverage from FR2 broadcasting. Consequently, FR1 can overlap FR2. To generate system efficiencies, the FR1 and FR2 spectrums can be combined by carrier aggregation (CA) and/or dual connectivity (DC). Thus, a hybrid approach can combine use of both CA and DC, based on radio access network instructions and radio frequency conditions experienced by a user equipment device as it transitions between CA and DC coverage areas.

Facilitation of dynamic spectrum aggregation for 5G or other next generation network

Concepts and technologies disclosed herein are directed to millimeter wave ('mmWave') idle channel optimization. According to one aspect disclosed herein, an antenna system can include an antenna array that is configured in a first antenna configuration. The antenna system can generate and send downlink beams directed towards a network edge. A beam index scanner operating at the network edge can scan the downlink beams to determine beam index scanner data for the first antenna configuration. The beam index scanner can send the bream index scanner data to an antenna technician device. The beam index scanner data can indicate that a downlink channel provided by the downlink beams is not optimized. The antenna system can configure the antenna array in a new antenna configuration in an attempt to optimize the downlink channel provided by the downlink beams.

Millimeter wave idle channel optimization

Utilization of collected crowd-sourced access point quality and selection data for intelligent network selection can optimize access point device selection. A cloud-based application can be utilized in conjunction with a mobile device to build a database of access point quality and thresholds suitable for real-time and other jitter-sensitive services. In one embodiment, a first mobile device can receive access point data associated with a second mobile device. The access point data associated with the second mobile device can then inform the first mobile device on whether to communicate with the access point device or utilized cellular communication.

Utilization of crowd-sourced access point data for 5G or other next generation network

A more efficient network can be achieved using channel allocation strategies within a wireless network. A network device can receive several data points from a mobile device including resource request data, access condition data, and location data. Once the network device has received the aforementioned data points, the network device can identify channels that are conducive to a heightened quality of service for a resource being requested based on a signal attenuation associated with the channel. The network device can then facilitate a channel selection in response to an assessment of the data points and identifying a channel for the resource.

Facilitation of channel selection within a wireless network

The technologies described herein are generally directed toward facilitating indicating frequency and time domain resources in communication systems with multiple transmission points. According to an embodiment, a system can comprise a processor, a base transceiver station, and a memory that can store executable instructions that, when executed by the processor, can facilitate performance of operations. The operations can include receiving a first signal. The operations can further include combining the first signal with a second signal resulting in a combined signal, wherein the first signal can be combined using a different weight than is applied to the second signal. The operations can further include broadcasting by an antenna of the base transceiver station, the combined signal.

Reducing interference by combining signals at different strengths and transmitting the combined signal from an antenna

When frequency range (FR)1 (e.g., Sub6Ghz radio coverage), and FR2 (e.g., mmW coverage) are present in a given area, there can be a broader coverage from FR1 broadcasting in addition to targeted coverage from FR2 broadcasting. Consequently, FR1 can overlap FR2. To generate system efficiencies, the FR1 and FR2 spectrums can be combined by carrier aggregation (CA) and/or dual connectivity (DC). Thus, a hybrid approach can combine use of both CA and DC, based on radio access network instructions and radio frequency conditions experienced by a user equipment device as it transitions between CA and DC coverage areas.

Growing community of inventors

Coral Springs, FL, United States of America

Kurt Donald Huber