Apple Inc.

Intel Corporation

Intel IP Corporation

Qian Li

Geng Wu

Dawei Ying

Lili Wei

Hassan Ghozlan

Zongrui Ding

Gang Xiong

Gabriel Arrobo Vidal

Huaning Niu

Yushu Zhang

Youn Hyoung Heo

Carlos Cordeiro

Alexander Sasha Sirotkin

Murali Narasimha

Satish Chandra Jha

Guangjie Li

Ching-Yu Liao

Lu Lu

Sudeep K Palat

Daewon Lee

Yaser M Fouad

Joonbeom Kim

Yujian Zhang

Jaemin Han

Apostolos Papathanassiou

Vesh Raj Sharma Banjade

Xiaoyun May Wu

Andreas Schmidt

Yongjun Kwak

Candy Yiu

Alexandre Saso Stojanovski

Puneet K Jain

Sangeetha L Bangolae

Pingping Zong

Seunghee Han

Yang Tang

Alexei Vladimirovich Davydov

Sergey Panteleev

Martin Hans

Michael Faerber

Dmitry Belov

Thomas Luetzenkirchen

Hong He

Mo-Han Fong

Jie Cui

Hwan-Joon Kwon

Debdeep Chatterjee

Alexey Vladimirovich Khoryaev

Maik Bienas

Jing Zhu

Jeongho Jeon

Carlos Horacio Aldana

Kathiravetpillai Sivanesan

Mikhail S Shilov

Seau Sian Lim

Andrey Chervyakov

Anthony Lee

Hua Li

Sergey D Sosnin

Fatemeh Hamidi-Sepehr

S M Iftekharul Alam

Necati Canpolat

Binita Gupta

Kuilin Clark Chen

Abhijeet Ashok Kolekar

Yi Zhang

Dae Won Lee

Ned M Smith

Yuan Zhu

Hyejung Jung

Joonyoung Cho

Joey Chou

Bharat Shrestha

Rui Huang

Richard Charles Burbidge

Gregory Vladimirovich Morozov

Yi Guo

Guotong Wang

Ozgur Oyman

Wenting Chang

Andrew J Herdrich

Honglei Miao

Yizhi Yao

Srikathyayani Srikanteswara

Robert Zaus

Farid Adrangi

Sameer Pawar

Avik Sengupta

Eve M Schooler

Yuhan Zhou

Dario Sabella

Rameshkumar G Illikkal

Christian Ibars Casas

Slawomir Putyrski

David Arditti Ilitzky

Chang Hong Shan

Shuang Tian

Feng Zhou

Maria E Ramirez Loaiza

Various embodiments generally may relate to the field of wireless communications. For example, some embodiments may relate to enabling augmented computing as a service or network capability for sixth-generation (6G) networks. For example, some embodiments may be directed to the operation of a compute control client (Comp CC) at the UE side, and a compute control function (Comp CF) and compute service function (Comp SF) at the network side, which are referred to herein as 'compute plane' functions to handle computing related control and user traffic.

Computing workload management in next generation cellular networks

This disclosure relates to embodiments broadcasting timing misalignment (TΔ or T_ delta or Tdelta) information in a fifth generation (5G) new radio (NR) integrated access and backhaul (IAB) network. Tdelta information associated with an IAB node is determined based on a downlink (DL) transmit (TX) timing associated with the IAB node and an uplink (UL) receive (RX) timing associated with the IAB node. A determination is made whether the Tdelta information is to common to at least one child node associated with the IAB node and at least one child user equipment (UE) associated with the IAB node. A message having the Tdelta information is generated in response to the determination that the Tdelta information is common to at least one child node associated with the IAB node and at least one child UE associated with the IAB node. The message is broadcast to the child nodes associated with the IAB node and the child UEs associated with the IAB node.

Broadcasting schemes of Tdelta information in fifth generation (5G) new radio (NR) integrated access and backhaul (IAB) network

Embodiments of a system and method for dual connectivity for device to vehicle or vehicle to vehicle communication in a Wireless Network are generally described herein. In some embodiments, processing circuitry may determine a quality of service (QoS) level for data to be transmitted over a first radio access technology (RAT) connection and determine a QoS indicator from the QoS level, the QoS indicator identifying a dual connectivity backup transmission, the dual connectivity backup transmission including a hot, warm, or cold backup. In some embodiments, transceiver circuitry may attempt to transmit the data using a first transmission mode, the first transmission mode using the first RAT connection and the data including the QoS indicator and retransmit, in response to the attempt failing, the data using a second transmission mode.

Dual connectivity for reliability

The present invention relates to an apparatus comprising: memory to store policy statement information for a plurality of radio access network (RAN) automation applications (rApps); and processing circuitry, coupled with the memory, to: retrieve the policy statement information from the memory, wherein the policy statement information includes respective policy scope identifiers for respective rApps in the plurality of rApps; identify a conflict associated with common or overlapping policy scope identifiers between two or more rApps from the plurality of rApps; modify one or more A1 policies associated with an A1 interface connecting a non-real-time (non-RT) RAN intelligence controller (RIC) and a near-real-time (near-RT) RIC to resolve the conflict; and notify the two or more rApps of the modification of the one or more A1 policies.

A1 policy functions for open radio access network (O-RAN) systems

Embodiments of the present disclosure describe methods and apparatuses for measurements and reports in integrated access and backhaul networks.

Inter-integrated access and backhaul node cross-link interference measurement and reporting

Some embodiments of this disclosure include apparatuses and methods for making a service request in Information Centric Networking (ICN) for next generation cellular networks. The apparatuses and methods can include at least generating, by a user equipment (UE), a service request message comprising access network (AN) parameters and service request parameters, wherein the AN parameters include a fifth generation-system architecture evolution-temporary mobile subscriber entity (5G-S-TMSI) parameter, a selected public land mobile network (PLMN) identifier, or an establishment cause; and transmitting, by the UE, the service request message to a next-generation NodeB (gNB).

Service request procedures in information centric networking for next generation cellular networks

Resource allocation is provided for an integrated access and backhaul (IAB) network, such as a distributed unit (DU) of an IAB. Methods and systems for allocating resources include allocating a first cell-specific pattern of downlink-flexible-uplink (DL-F-UL) availability for one or more slots, allocating a second cell-specific pattern of DL-F-UL availability for the one or more slots. The IAB DU can signal one or more of the first and second cell-specific patterns to an other IAB DU. At least one of the first cell-specific pattern and the second cell-specific pattern defines a slot format different from a DL-F-UL format. Slot format configuration (e.g., semi-static or dynamic SFI) are provided to support space division multiplexing/spatial multiplexing (SDM).

Slot formats for semi-static download-uplink configuration and dynamic slot format indication in integrated access and backhaul networks

Disclosed are methods, systems, apparatus, and computer programs for communicating new random access channel (RACH) configurations for a node in an integrated access and backhaul (IAB) network. In one aspect, a method includes receiving a Radio Resource Control (RRC) message from the IAB node; determining, based on the RRC message, a new random access channel (RACH) configuration; and in response to determining the new RACH configuration, initiating a random access procedure with the IAB node using the new RACH configuration.

Random access channel configuration in an integrated access and backhaul network

Apparatuses for non real-time (Non-RT) radio access network intelligence controller (RIC) and Near-RT RIC services for machine learning (ML) model management in an open radio access network (O-RAN) are disclosed. The services include ML model monitoring, getting and putting ML models from and to an AI-ML producer and an AI-ML consumer, and terminating the use of an ML mode. The ML model monitoring includes the AI-ML consumer sending monitoring data to the AI-ML producer and the AI-ML producer processing the monitoring data and taking actions based on the monitoring data. The services may be performed over the AI interface using HTTP.

ML model management in O-RAN

A next generation NodeB (gNB) implements a radio access network (RAN) convergence functionality for new radio (NR) and wireless local area network (WLAN) access, the gNB further implementing a split architecture comprising a central unit (CU) and a distributed unit (DU) for each of the NR access and WLAN access. The gNB receives a data packet for transmission to a user equipment (UE) implementing the RAN convergence functionality, the data packet comprising one of a control plane (CP) packet or a user plane (UP) packet. The gNB splits the data packet via a convergence layer residing on the NR CU or a convergence layer residing on the WLAN CU and transmits the split data packet over the NR access and the WLAN access.

Mutual anchoring and traffic distribution in a converged RAN integrating NR and Wi-Fi access

Systems, methods, and circuitries are provided for communicating DU resource configuration information of a child IAB node to a parent IAB node. An example method includes identifying distributed unit (DU) resource configuration information for an IAB node device functioning as an IAB node in the IAB network, wherein the IAB node is associated with a parent IAB node, and transmitting the DU resource configuration information to the parent IAB node.

Child distributed unit resource configuration information signaling in 5G-NR integrated access backhaul network

A data-centric network and non-Real-Time (RT) RAN Intelligence Controller (RIC) architecture are described. The data-centric network architecture provides data plane functions (DPFs) that serve as a shared database for control functions, user functions and management functions for data plane resources in a network. The DPFs interact with control plane functions, user plane functions, management plane functions, compute plane functions, network exposure functions, and application functions of the NR network via a service interface. The non-RT RIC provides functions via rApps, manages the rApps, performs conflict mitigation and security functions, monitors machine learning (ML) performance, provides a ML model catalog that contains ML model information, provides interface terminations and stores ML data and Near-RT RIC related information in a database. An ML training host trains and evaluates ML models in the catalog, obtains training and testing data from the database, and retrains and updates the ML models.

Data-centric service-based network architecture

Some embodiments of this disclosure include apparatuses and methods for determining synchronization signal block (SSB) periodicity for cell reselection. In some embodiments, user equipment (UE) may establish a first connection with a first integrated access and backhaul (IAB) node using a first SSB periodicity. The UE may perform a cell reselection process and determine whether a number of candidate IAB nodes include a candidate IAB node with a previously stored candidate SSB periodicity corresponding to the candidate IAB node. If the UE identifies a candidate SSB periodicity, the UE may establish a second connection with the candidate IAB node using the candidate SSB periodicity. If the UE does not identify a previously stored candidate SSB periodicity, the UE may establish a second connection with a second IAB node using a second SSB periodicity that is less than the first SSB periodicity.

Synchronization signal block periodicity for cell reselection

This disclosure describes systems, methods, and devices related to service function chaining in wireless networks. A communications system may include a communication control function to select one or multiple communication service functions associated with establishing service function chaining (SFC) services for telecommunications; a service orchestration and chaining function (SOCF) to establish the SFC services; and a service orchestration exposure function (SOEF) to expose the SFC services to an application function (AF) of the system.

Enhanced service function chaining in next generation cellular networks

An apparatus of an Integrated Access and Backhaul (IAB) node includes processing circuitry coupled to a memory. To configure the IAB node for resource allocation within an IAB network, the processing circuitry is to decode radio resource control (RRC) signaling from a central unit (CU) function of an IAB donor node. The RRC signaling configures first time-domain resources for a parent backhaul link between a mobile termination (M) function of the IAB node and a distributed unit (DU) function of a parent IAB node, and second time-domain resources for a child backhaul link between a DU function of the IAB node and a MT function of a child IAB node. Uplink data is encoded for transmission to the parent IAB node based on the first time-domain resources. Downlink data is encoded for transmission to the child IAB node based on the second time-domain resources.

Resource allocation in IAB networks

Growing community of inventors

Beaverton, OR, United States of America

Qian Li