Intel Corporation

Apple Inc.

Samsung Electronics Co., Ltd.

Alcatel Lucent

Intel University

Intel IP Corporation

Kathiravetpillai Sivanesan

Rath Vannithamby

Satish Chandra Jha

Ali Taha Koc

S M Iftekharul Alam

Kuilin Clark Chen

Mohammad Mamunur Rashid

Sridhar G Sharma

Liuyang L Yang

Vesh Raj Sharma Banjade

Ignacio Javier Alvarez

Yujian Zhang

Lai King Tee

Leonardo Gomes Baltar

Ned M Smith

Srikathyayani Srikanteswara

Venkatesan Nallampatti Ekambaram

Justin E Gottschlich

Maruti Gupta

Subramanian Vasudevan

Zongrui Ding

Gabriel Arrobo Vidal

SaiRamesh Nammi

Jing Zhu

David Israel Gonzalez Aguirre

Ashvin H Chheda

Eve M Schooler

Xiruo Liu

Neng Wang

Peiying Zhu

Hassnaa Moustafa

Debabani Choudhury

Maruti Gupta Hyde

Candy Yiu

Dong-seek Park

Christian Maciocco

Vallabhajosyula S Somayazulu

Young-Kwon Cho

Jialin Zou

Eun-Taek Lim

Lu Lu

Ravikumar Balakrishnan

Youn Hyoung Heo

Manoj R Sastry

Shilpa Talwar

Qian Li

Hosein Nikopour

Do-Young Kim

Marcio Rogerio Juliato

Rafael Misoczki

Jeffrey Sedayao

Hong He

Yushu Zhang

Dae Won Lee

Gang Xiong

Alexei Vladimirovich Davydov

Jie Cui

Debdeep Chatterjee

Muthaiah Venkatachalam

Minyoung Park

Joonyoung Cho

Yongjun Kwak

Sergey Panteleev

Joey Chou

Markus Dominik Mueck

Rui Huang

Bharat Shrestha

Alexander Sasha Sirotkin

Richard Charles Burbidge

Gregory Vladimirovich Morozov

Yi Guo

Puneet K Jain

Jeongho Jeon

Geng Wu

Alexander F Heinecke

Seau Sian Lim

Ho-Kyu Choi

Andrey Chervyakov

Honglei Miao

Anthony Lee

Yizhi Yao

Sara S Baghsorkhi

Hua Li

Robert Zaus

Farid Adrangi

Ashok N Rudrapatna

Cheng Shan

Shabbir Ahmed

Christopher N Gutierrez

Meghashree Dattatri Kedalagudde

Chan-Byoung Chae

Jaemin Han

Sebastian Schoenberg

Dawei Ying

Jason Martin

Avik Sengupta

Ching-Yu Liao

Baowei Ji

Vuk Lesi

Yuhan Zhou

Systems and techniques for misbehavior processing in connected vehicle networks such as a vehicle-to-everything (V2X) communication environment are described herein. A misbehavior report may be received by a local misbehavior agent from a node operating on a vehicle communication network. The local misbehavior agent may be responsible for a geographic area in which the node is located. The misbehavior report may be corroborated using the misbehavior report and evidence of misbehavior of a subject node of the misbehavior report. A revocation recommendation may be generated for the subject node based on the corroboration. The revocation recommendation may be transmitted to a misbehavior authority operating on the vehicle communication network.

Misbehavior processing in connected vehicle networks

Disclosed herein is a roadside unit with a radio frontend port configured to receive a first signal representing a radiofrequency transmission according to a first radio communication protocol, to receive a second signal representing a radiofrequency transmission according to a second radio communication protocol. A first processing subsystem configured to execute a first baseband process of the first radio communication protocol on the first signal and to generate a first output signal as an output of the first baseband process. A second processing subsystem configured to execute a baseband process of the second radio communication protocol on the second signal and to generate a second output signal as an output of the second baseband process. The first processing subsystem is a first software containerization or a first machine virtualization of the processor, wherein the second processing subsystem is a second software containerization or a second machine virtualization of the processor.

Roadside unit, a processing module for processing a roadside unit signal, and a method of processing a roadside unit signal

The present disclosure is related to vehicle-to-everything (V2X) and Intelligent Transport System (ITS) communications technologies, and in particular, to misbehavior detection and misbehavior reporting services for Collective Perception Messages (CPMs). The misbehavior detection mechanisms include one or more data consistency checks, including a multi-step systematic data consistency check within individual CPMs, across multiple CPMs from the same transmitter, and across multiple CPMs from different transmitters. Potential misbehaviors are reported to a misbehavior authority in one or more misbehavior reports.

Misbehavior detection using data consistency checks for collective perception messages

A non-transitory computer-readable storage medium stores instructions to configure a base station for user equipment (UE) authentication in a wireless network and to cause the base station to perform an operation comprising decoding configuration signaling received from a PHY security function (PSF) of the wireless network. The configuration signaling includes a request for collection of a plurality of signal samples from the UE, the UE authenticated based on successful completion of a first authentication process. A response message is encoded for transmission to the PSF. The response message includes the plurality of UE signal samples. A trained machine learning model received from the PSF is decoded. The trained machine learning model associates the authenticated UE with an RF signature of the UE. The RF signature is based on the plurality of signal samples. A second authentication process of the UE is performed based on the trained model.

Adaptive and hierarchical network authentication framework

Maneuver Coordination Services (MCS) may be used in various implementations of vehicular networks. Emergency Group Maneuver Coordination (EGMC) may be used for detected unexpected safety-critical situations (USCS) on the road. EGMC provides cooperative maneuver coordination among a group of vehicles to ensure safer collective actions in the case of USCS. An MCS and EGMC may utilize a Maneuver Coordination Message (MCM) based on procedures for the Generation and Transmission of MCM with reduced communication overhead.

Maneuver coordination service in vehicular networks

An apparatus and system to mitigate non-genuine handovers are described. The handovers include handovers based on fake measurements and handovers to malicious cells. To mitigate these, a mitigation procedure is initiated when excessive handovers are detected. Location information obtained from the UE, estimation of PHY layer properties by the serving and/or target cell, or AI modeling of the best serving cell at the UE location is used to determine whether the handover is valid. If not, the handover is canceled and the UE is stopped from initiating new handovers for a specified time, the UE may be instructed to perform re-authentication with the network, and/or the serving cell recommends to the network authentication entity to revoke the UE authentication. To ensure that the target cell is legitimate, an AI model is used to classify the target cell as known/unknown and the result sent to the network in NAS signaling.

Physical layer techniques to mitigate the handover process vulnerabilities

A computing node to implement a management entity in a CP-based network. The node including processing circuitry configured to encode an inquiry message requesting information on CPS capabilities. Response messages are received from a set of sensing nodes of a plurality of sensing nodes in response to the inquiry message. The response messages include the information on the CPS capabilities of the set of sensing nodes. A notification message indicating selecting of a sensing node as a sensing coordinator is encoded for transmission. Sensed data received in a broadcast message from the sensing coordinator is decoded. The sensed data including data associated with one or more non-V2X capable sensing nodes.

Occupancy grid map computation, V2X complementary sensing, and coordination of cooperative perception data transmission in wireless networks

The present disclosure is related to Intelligent Transport Systems (ITS), and in particular, to Vulnerable Road User (VRU) basic services (VBS) of a VRU ITS Station (ITS-S). Implementations of how the VBS is arranged within the facilities layer of an ITS-S, different conditions for VRU Awareness Message (VAM) dissemination, and format and coding rules of the VAM generation.

Vulnerable road user basic service communication protocols framework and dynamic states

The present disclosure describes mechanisms to manage session continuity for edge computing services for edge service consumers. The session management mechanisms include continuity or handing over edge service sessions between edge computing platforms in a same edge compute cluster and between edge computing platforms in different edge compute clusters. The session management mechanisms include edge computing platform switching/handover for user equipment capable of utilizing multiple access network connections and/or multiple access technologies. The described solutions can provide edge service session continuity between connected vehicles and road side units and/or edge compute nodes.

Managing session continuity for edge services in multi-access environments

Systems and techniques for mobility-as-a-service for user experience are described herein. An orchestration log may be maintained that includes current orchestration data. An orchestration backup record may be generated that includes alternate MaaS nodes on the MaaS network. It may be determined that connectivity is lost to a first orchestration container hosted by a first MaaS node. An orchestration container is generated using the orchestration log to maintain orchestration functionality. An available second MaaS node is identified from the alternate MaaS nodes. The orchestration container may be transferred to the second MaaS node.

Mobility-as-a-service for user experience

The present disclosure describes local breakout for edge computing systems, wherein the local breakout selectively routes the traffic from/to a user equipment between an edge compute node or some other service such as a core network, cloud computing service, or the like. Packets related to microservices that are offered by the edge compute node are routed to the edge compute node instead of routing those packets to the core network, and packets that are not related to the microservices provided by the edge compute node are routed to the core network or to another network such as a data network or cloud computing service. In these ways, the local breakout mechanisms provide low latency and reduced network resource consumption for the microservices and decreased data traffic load on the core network.

Edge computing local breakout

Techniques are disclosed to increase the safety of vehicles travelling in a vehicle platoon. These techniques include the utilization of a comprehensive safety framework such as a safety driving model (SDM) for the platoon control systems. In contrast to the conventional approaches, the use of the SDM model allows for platoon vehicle control systems to consider the acceleration/deceleration capabilities of the vehicles to calculate minimum safe longitudinal distances between the platoon vehicles. The disclosed techniques may utilize the periodicity of platoon messages as well as other parameters to improve upon platoon vehicle control and safety.

Cooperative adaptive cruise control (CACC) system for control of connected and autonomous vehicle (CAV) platoons

The present disclosure is related to Intelligent Transport Systems (ITS), and in particular, to service dissemination basic services (SDBS) and/or collective perception service (CPS) of an ITS Station (ITS-S). Implementations of how the SDBS and/or CPS is arranged within the facilities layer of an ITS-S, different conditions for service dissemination messages (SDMs) and/or collective perception message (CPM) dissemination, and format and coding rules of the SDM/CPS generation are provided.

Collective perception service enhancements in intelligent transport systems

Disclosed are embodiments that provide a transportation environment data service. The transportation environmental data service includes harvesting services that crawl roadside infrastructure solutions to obtain sensor data collected from sensors physically positioned at the roadside infrastructure. In some cases, the roadside infrastructure solutions perform additional processing on the sensor data. For example, some roadside infrastructure performs object detection and/or object recognition. When encountering these solutions, the edge or harvesting service also collects the object detection and/or object recognition information. Customers can subscribe to various data services provided by the transportation environment data service. For example, some subscribers indicate an interest in any updates of environmental data for a particular region. Other subscribers are interested in video data associated with any vehicular accidents detected by the transportation environment data service.

Transportation environment data service

Embodiments described herein relate generally to a communication between a user equipment ('UE') and a plurality of evolved Node Bs (“eNBs”). A UE may be adapted to operate in a dual connected mode on respective wireless cells provided by first and second eNBs. The UE may be adapted to estimate respective power headroom (“PHR”) values associated with simultaneous operation on the first and second wireless cells. The UE may cause the first and second PHR estimates to be transmitted to both the first and second eNBs. The first and second eNBs may use these estimates to compute respective uplink transmission powers for the UE. Other embodiments may be described and/or claimed.

Power headroom reporting with dual connectivity

Growing community of inventors

Portland, OR, United States of America

Kathiravetpillai Sivanesan