At&t Intellectual Property I, L.p.

Purdue Research Foundation

New York University

University College Cork

At&t Corp.

Columbia University

New Jersey Institute of Technology

Rittwik Jana

Christopher W Rice

John F Murray

Vaneet Aggarwal

Nemmara K Shankaranarayanan

Shu Shi

Yih-Farn Robin Chen

Mostafa Tofighbakhsh

Vijay Gopalakrishnan

Deva-Datta Sharma

Bernard S Renger

Mazin E Gilbert

Bo Han

Emir Halepovic

David Crawford Gibbon

Kadangode K Ramakrishnan

Sarat Puthenpura

Rakesh Sinha

Lusheng Ji

Jeffrey Erman

Jin Wang

Kaustubh Joshi

Giuseppe Di Fabbrizio

Divesh Srivastava

Gueyoung Jung

Matti A Hiltunen

Arunabha Ghosh

Milap V Majmundar

Paul Edward Smith, Jr

Zhengye Liu

Reuben Klein

Feng Qian

Gerald Michael Karam

Behzad Shahraray

Lee Begeja

Zhu Liu

Jeffrey Aaron

Andrea Basso

Oliver Spatscheck

James Fan

Subhabrata Bapi Sen

Robert J Hall

Bin Wei

Serban Jora

Varun Gupta

Shraboni Jana

Bogdan Ungureanu

Syed Anwar Aftab

Yu Zhou

Ron Shacham

Dinesh Bharadia

Thomas Kirk

Dhruv Gupta

Michael Hwang

Vinay Anant Vaishampayan

Vaidyanathan Ramaswami

Avi Zahavi

Bo Yan

Ashutosh Sabharwal

Ping-Fai Yang

Christopher Rath

Xuan Tuyen Tran

Rajesh Krishna Panta

Rajarajan Sivaraj

Daniel Leon Stern

Sam John

Samrat Bhattacharjee

Eric Noel

Cagatay Buyukkoc

Edward G Amoroso

Ioannis Broustis

Weihua Ye

Xu Chen

Balagangadhar Bathula

Manoop Talasila

Cormac John Sreenan

Laurie Bigler

Matteo Varvello

Edward Daniels

Barbara Laing

Bharath Balasubramanian

Michael Rabinovich

Tan Xu

Amy Ruth Reibman

Seungjoon Lee

Slawomir Mikolaj Stawiarski

Hung-Hsiang Jonathan Chao

Arthur L Zaifman

Yong Liu

Shivendra S Panwar

Guy Jacobson

Zhen Xiao

Yang Xu

Yennun Huang

Vishal Misra

Wen-Ling Hsu

Kevin Donnellan

Daniel Rubenstein

Tae Won Cho

Howard Karloff

The technologies described herein are generally directed to modeling radio wave propagation in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include, for a network application, identifying, by a system comprising a processor, a characteristic value of a performance characteristic associated with an uplink connection enabled via a network of a user equipment to application server equipment hosting the network application. The method can further include, based on the characteristic value and a criterion, selecting, by the system, a first packet size for the uplink connection. The method can further include communicating, by the system, to the user equipment, the first packet size for use with the uplink connection.

Streaming augmented reality data in a fifth generation (5G) or other next generation network

The described technology is generally directed towards wireless communications for vehicle collision response. Devices onboard vehicles can wirelessly exchange information in response to detecting a collision. Public encryption keys can be exchanged, and exchanged information can optionally be encrypted using a received public encryption key. Exchanged information can include vehicle identification information and collision information. The collision information can furthermore be certified using a vehicle's private encryption key.

Wireless communications for vehicle collision response

A model-driven system automatically deploys a virtualized service, including multiple service components, on a distributed cloud infrastructure. A master service orchestrator causes a cloud platform orchestrator to retrieve a cloud services archive file, extract a cloud resource configuration template and create cloud resources at appropriate data centers as specified. The master service orchestrator also causes a software defined network controller to retrieve the cloud services archive file, to extract a cloud network configuration template and to configure layer 1 through layer 3 virtual network functions and to set up routes between them. Additionally, the master service orchestrator causes an application controller to retrieve the cloud services archive file, to extract a deployment orchestration plan and to configure and start layer 4 through layer 7 application components and bring them to a state of operational readiness.

Model driven process for automated deployment of domain 2.0 virtualized services and applications on cloud infrastructure

The technologies described herein are generally directed to modeling radio wave propagation in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include, for a network application, identifying, by a system comprising a processor, a first performance characteristic of first base station equipment, wherein the first base station equipment is actively communicating with a user equipment via a first network connection. The method can further include, based on the first performance characteristic being in a condition in relation to a first threshold, determining, by the system, to execute a handover of the user equipment to a second network connection with second base station equipment, resulting in a handover determination. Further, the method can include, based on the handover determination, facilitating, by the system, executing the handover of the user equipment to the second network connection.

Using dynamic thresholds for non-mobility handovers in a fifth generation (5G) or other next generation network

The described technology is generally directed towards a cellular network area optimizer. The area optimizer observes cellular network conditions at multiple radio access network (RAN) nodes within a target area. Based on observed conditions, the area optimizer applies a set of parameter values at the multiple RAN nodes. The set of parameter values enhances the overall throughput, while maintaining or improving connection retainability and accessibility, of the multiple RAN nodes under the observed conditions. The area optimizer learns different sets of parameter values to apply in response to different observed conditions by making parameter value adjustments and observing the effect of the adjustments on overall throughput of the RAN nodes in the target area.

Cellular network area optimizer

The described technology is generally directed towards a transport protocol for latency sensitive applications. The disclosed transport protocol is 'semi-reliable' in that it allows for specification of an importance of data being transmitted, thereby allowing important data to be sent reliably, while other data can be dropped if necessary, e.g., under bad network conditions. A deadline can be specified for such other data, and if the other data cannot be sent prior to the deadline, it can be dropped. Furthermore, the disclosed transport protocol can allow for early discovery of network jitter. A client device can send regular acknowledgments which identify most recently received data packets as well as a number of “heartbeat transmissions” received at the client device. A server device can use the acknowledgments to discover and respond to jitter.

Transport protocol for latency sensitive applications

Facilitating geo-distributed dynamic network system for ubiquitous access to multiple private networks in advanced networks (e.g., 4G, 5G, and beyond) is provided herein. Operations of a method can comprise establishing, by a system comprising a processor, a first communication link between a first network device and group of devices connected via a private network connection. The method also can comprise establishing, by the system, a second communication link between the first network device and a second network device. The second network device can be included in a group of network devices associated with a communication network provider. Further, the second network device can facilitate communication with a communication device.

Facilitating a geo-distributed dynamic network system for ubiquitous access to multiple private networks

Aspects of the subject disclosure may include, for example, obtaining predicted available bandwidths for an end user device, monitoring buffer occupancy of a buffer of the end user device, determining bit rates for portions of media content according to the predicted available bandwidths and according to the buffer occupancy, and adjusting bit rates for portions of media content according to the predicted available bandwidths and according to the buffer occupancy during streaming of the media content to the end user device over a wireless network. Other embodiments are disclosed.

Method and system for managing service quality according to network status predictions

An artificial intelligence (AI) automation to improve network quality based on predicted locations is provided. A method can include training, by a first device comprising a processor and according to model configuration parameters received from a second device that is not the first device, a local machine learning model with training data derived from first location data collected by the first device; transmitting, by the first device to the second device, anonymized model features associated with the local machine learning model; in response to the transmitting of the anonymized model features, receiving, by the first device from the second device, an aggregated machine learning model; and estimating, by the first device, a future position of the first device by applying the aggregated machine learning model to second location data collected by the first device.

Artificial intelligence automation to improve network quality based on predicted locations

Aspects of the subject disclosure may include, for example, a device including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving signal to noise and interference ratio (SINR) measurements from a cell for two or more uplink carriers associated with a mobile device; determining an optimal uplink carrier from the two or more uplink carriers based on plural parameters, wherein the plural parameters include the SINR measurements; selecting the optimal uplink carrier from the two or more uplink carriers; and sending the optimal uplink carrier selected to the cell, wherein the mobile device uses the optimal uplink carrier for uplink transmissions. Other embodiments are disclosed.

Supplementary uplink carrier selection by radio access network intelligent controller

Aspects of the subject disclosure may include, for example, obtaining a model of a communication network, applying first data to the model to generate an updated model, processing the updated model to establish a first control, enabling first communications in the communication network in accordance with the first control, obtaining first parametric data regarding the first communications in the communication network that are based on the first control, processing the first parametric data in accordance with the updated model to generate an updated first control, and enabling second communications in the communication network in accordance with the updated first control. Other embodiments are disclosed.

Method and apparatus for controlling disaggregated radio access networks

Aspects of the subject disclosure may include, for example, receiving, over a communication network, a plurality of requests for frames of video content to provide to a mobile device. Further embodiments can include determining a first portion of the plurality of requests are for pre-fetch frames of the video content, and providing, over the communication network, the pre-fetch frames to the mobile device over a default bearer path. Additional embodiments can include determining a second portion of the plurality of requests are for emergent frames of the video content, and providing, over the communication network, the emergent frames to the mobile device over a dedicated bearer path. Other embodiments are disclosed.

Methods, systems, and devices for providing service differentiation for different types of frames for video content

Aspects of the subject disclosure may include, for example, a processing system of a communication node routing data packets for a first streaming session between a viewer node of a plurality of viewer nodes and a content streaming server through the communication node without interrupting delivery of content data to the viewer node, establishing a second streaming session with the content streaming server to receive the content data, creating a first and second replacement connections by imitating a connections with the content streaming server and the viewer node, receiving a control packet over the second streaming session from the content streaming server, and splitting the first streaming session responsive to receiving the control packet. Other embodiments are disclosed.

Synchronizing and dynamic chaining of a transport layer network service for live content broadcasting

Full-duplex communications are provided by modifying the Media Access Control sub-layer of communication node protocols. The modification allows communication nodes to communicate with one another in full-duplex, where each node transmits and receives data simultaneously with other nodes in a single frequency. A timing of the simultaneous data transmissions, acknowledgments, and short-interframe-space waiting periods can be determined based on network-allocation-vector data transmitted in association with request-to-send or clear-to-send signals.

System and method for full-duplex media access control using request-to-send signaling

The described technology is generally directed towards a transport protocol for latency sensitive applications. The disclosed transport protocol is 'semi-reliable' in that it allows for specification of an importance of data being transmitted, thereby allowing important data to be sent reliably, while other data can be dropped if necessary, e.g., under bad network conditions. A deadline can be specified for such other data, and if the other data cannot be sent prior to the deadline, it can be dropped. Furthermore, the disclosed transport protocol can allow for early discovery of network jitter. A client device can send regular acknowledgments which identify most recently received data packets as well as a number of 'heartbeat transmissions' received at the client device. A server device can use the acknowledgments to discover and respond to jitter.

Growing community of inventors

Montville, NJ, United States of America

Rittwik Jana