Abstract: Systems and techniques for cross-layer automated fault tracking and anomaly detection are described herein. Anomaly data may be obtained from a plurality of layers of a network. Elements of the anomaly data may be identified that correspond to a data flow of an application executing on the network. An artificial intelligence model may be trained using the elements of the anomaly data to generate an impact score for the application. The impact score may be generated for the application by evaluating current network metrics using the artificial intelligence model. An operational component of the network may be modified based on the impact score.

Abstract: System and techniques for geographic routing are described herein. A node receives a data packet that includes map data, a sequence of geographic areas to a requestor, and a target geographic area. The node may then determine that it is within the target geographic area and start a transmit timer based on a next-hop geographic area. Here, the next-hop geographic area is determined from the sequence of geographic areas in the data packet. The node may then counts how many other nodes from the geographic area sent data packets while the transmit timer is running. When the transmit timer expires, the node may transmit a modified data packet when the number of data packets is less than a predefined threshold. Here, the modified data packet is the data packet updated to include local map data and the next-hop geographic area.

Abstract: Technology for a user equipment (UE) to perform long-term evolution (LTE) and Wireless local area network (WLAN) aggregation (LWA) connection procedures within a wireless communication network is disclosed. The UE can determine to suspend communication on a wireless local area network (WLAN) of one or more protocol data units (PDUs) for a LWA session without terminating the LWA session. The UE can process, for transmission to an eNodeB, a request to suspend communication of the one or more PDUs on the WLAN to enable the eNodeB to schedule the one or more PDUs for transmission to the UE through a cellular interface without terminating the LWA session.

Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.

Abstract: Systems and methods of using machine-learning to improve communications across different networks are described. A CIRN node identifies whether it is within range of a source and destination node in a different network using explicit information or a machine-learning classification model. A neural network is trained to avoid interference using rewards associated with reduced interference or retransmission levels in each network or improved throughput at the CIRN node. A machine-learning scheduling algorithm determines a relay mode of the CIRN node for source and destination node transmissions. The scheduling algorithm is based on the probability of successful transmission between the source and destination nodes multiplied by a collaboration score for successful transmission and the probability of unsuccessful transmission of the particular packet multiplied by a collaboration score for unsuccessful transmission.

Abstract: A method for coordinating communication amongst a plurality of mobile devices, includes generating joint transmission information describing transmission information for use by the plurality of mobile devices in transmitting data related to a cooperative communication message to a destination node and instructing a mobile device to transmit a coordination message to the plurality of mobile devices, wherein the coordination message includes the joint transmission information.

Abstract: Briefly, in accordance with one or more embodiments, an apparatus of a user equipment (UE) comprises one or more baseband processors to generate a first set of one or more radio resource control (RRC) messages to create a packet data convergence protocol (PDCP) and RRC entity at a donor Fifth Generation evolved NodeB (DgNB), and to generate a second set of one or more RRC messages to create a radio link control (RLC) entity at a serving relay node (RN) to couple with the DgNB in a multi-hop relay network, and a memory to store the first set of one or more RRC messages or the second set of one or more RRC messages.

Abstract: An apparatus of a base station in a network may include a memory device and a processing device operatively coupled to the memory device. The processing device may process a message received at the base station from a macro-cell base station. The message may include a request to act as a relay for a user equipment (UE). The processing device may then determine that the base station is to act as a relay for the UE. The processing device may then generate a message comprising an indication that the base station accepted the request to act as a relay for the UE.

Abstract: A method of implementing distributed AI or ML learning for autonomous vehicles is disclosed. An AI or ML model specific to a location or a type of the location is generated at a vehicle. In response to a detection that the vehicle is within a proximity to a road side unit (RSU) associated with the location or the type of the location or the vehicle is within a proximity to an additional vehicle that is present or anticipated to be present at the location or the type of the location, causing an AI or ML model transmission to the additional vehicle or the RSU. Based on the causing the AI or ML model reception, causing deployment of an additional AI or ML model in the vehicle to optimize the vehicle for the location or the type of the location.

Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.

Abstract: Systems and methods provide cross-layer bearer splitting and cross-RAT retransmission in a RAN-based WLAN/WWAN integrated network. A link aggregation transmitter is configured to receive, from a WLAN stack lower layer protocol, a WLAN transmission confirmation signal and a WLAN congestion status, and to receive, from a WWAN stack lower layer protocol, a WWAN transmission confirmation signal and a WWAN congestion status. The link aggregation transmitter dynamically splits the bearer traffic across the WWAN link and the WLAN link based at least in part on the WLAN transmission confirmation signal, the WLAN congestion status, and the WWAN congestion status.

Abstract: System and techniques for information centric network (ICN) protocol for federated learning are described herein. An interest packet may be received on a first interface to start a federated learning round. Here, the interest packet includes a participant criterion and a federated learning round expiration. An entry, that includes the federated learning round expiration, is created in a pending interest table (PIT) for the interest packet. The interest packet is forwarded, in accordance with a forwarding information base (FIB), to a set of interfaces before the federated learning round expiration. When a data packet from a node, that meeting the participant criterion, is received in response to the interest packet, the data packet is forwarded on the first interface in accordance with the PIT entry.

Abstract: Methods, systems, and computer programs are presented for implementing Personalized Mobility as a Service (PMaaS) to improve transportation services delivery. One storage medium includes instructions for detecting, by a mobility as a service (MaaS) system, a request for a trip from a user device of a user. The storage medium further includes instructions for mapping, using a model executing on the machine, the user to a persona from a plurality of persona models. Each persona model has one or more characteristics associated with users of the MaaS system. Further yet, the storage medium includes instructions for determining trip parameters for the trip based on the persona mapped to the user, the trip parameters defining one or more trip segments for the trip, and instructions for providing trip parameters to the user device.

Abstract: Generally discussed herein are systems, devices, and methods for populating a cache in an information-centric network. A device of an ICN can include a content store including published content and attributes of the published content stored thereon, the attributes including at least two of a device from which the content originated attribute, a lineage attribute, and a service level agreement attribute, and content processing circuitry coupled to the content store, the content processing circuitry configured to manage the published content based on the attributes.

Abstract: Methods and apparatus to manage operation of variable-state computing devices using artificial intelligence are disclosed. An example computing device includes a hardware platform. The example computing device also includes an artificial intelligence (AI) engine to: determine a context of the device; and adjust an operation of the hardware platform based on an expected change in the context of the device. The adjustment modifies at least one of a computational efficiency of the device, a power efficiency of the device, or a memory response time of the device.

Abstract: Methods, apparatus, and computer-readable media are described to use multi-finger beamforming for multimeter wave communications. A base station associates with first and second user equipment. Weight sum rates are determined for the user equipment. Transmissions are scheduled to the user equipment based on the weight sum rates. Data is encoded for the first user equipment and transmitted based on the schedule. Data is encoded for the second user equipment and transmitted based on the schedule. The transmissions are multiplexed in the power domain.

Abstract: Uplink (UL) data splits between LTE and WLAN can be go supported in cellular networks. The split can be UE controlled or network controlled. Both UE and network controlled bearer split architectures can be supported. The reporting of Uplink Buffer Status (BSR) and the subsequent data allocation can depend on what option is supported by the network. For UE controlled UL data splits, the UE determines a traffic split ratio between LTE and WLAN. The split can be based on local link conditions. For network controlled UL data splits, the network (e.g. a Link Aggregation Scheduler at the eNB) is responsible for making bearer split decisions. The decisions can be based on link qualities, available traffic and quality of service (QoS) requirements of associated users. The split can be based on a per bearer threshold, an eNB configured ratio, or an implicit inference based on a UL grant.

Abstract: A RAN-based cellular integration architecture is described that eliminates or minimizes required core network support. A local access gateway (LA-GW) node, which may be a logical and physical node, may provide an interface, with a cellular base station, and may forward downlink and/or uplink local IP packets that are then redirected to the cellular link. Network Address Translation (NAT) and a “local access” field are used to support transmission of local access packets over the cellular link.

Abstract: System and techniques for information centric network (ICN) mobility management are described herein. A packet may be received, at a first network node positioned between a subscriber and a publisher of an ICN, for a second network node. Movement metrics for the second network node may also be received. The packet may then be transmitted to a third network node—selected from a plurality of network nodes based on the movement metrics—for delivery to the second network node.

Abstract: Briefly, in accordance with one or more embodiments, an apparatus of a user equipment (UE) comprises baseband circuitry including one or more processors to decode a secondary synchronization signal (SSS) or a beam reference signal (BRS) received from an evolved Node B (eNB) to select a Tier-1 sector for receiving downlink transmissions from the eNB, decode a downlink control channel message received from the eNB at one or more fixed time offsets after the UE decodes the SSS to obtain index information for the Tier-1 sector to identify the Tier-1 sector, and if the Tier-1 sector has changed initiate a random access procedure to select an updated Tier-1 sector, and generate an updated Tier-1 sector index message to report to the eNB.