US-20260128958-A1 - AI/ML Models in Wireless Communication Networks

US20260128958A1US 20260128958 A1US20260128958 A1US 20260128958A1US-20260128958-A1

Abstract

Embodiments provide a user device, UE, of a wireless communication network, the wireless communication network using one or more Artificial Intelligence/Machine Learning, AI/ML, models for one or more use cases, wherein the UE is configured or preconfigured with a plurality of AI/ML models for performing one or more certain operations, and wherein, dependent on one or more criteria, for performing the one or more certain operations, the UE is to switch from a first AI/ML model to a second AI/ML model, or deactivate one or more of the plurality of AI/ML models, or switch from a current operation mode to a new operation mode.

Inventors

Thomas Fehrenbach
Thomas Wirth
Baris GOEKTEPE
Thomas Schierl
Thomas Wiegand
Cornelius Hellge

Assignees

FRAUNHOFER-GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.

Dates

Publication Date: 20260507
Application Date: 20251003
Priority Date: 20230406

Claims (15)

1 . A user device, UE, of a wireless communication network, the wireless communication network using one or more Artificial Intelligence/Machine Learning, AI/ML, models for one or more use cases, wherein the UE is configured or preconfigured with a plurality of AI/ML models for performing one or more certain operations, and wherein, dependent on one or more criteria, for performing the one or more certain operations, the UE is to switch from a first AI/ML model to a second AI/ML model, or deactivate one or more of the plurality of AI/ML models, or switch from a non-AI/ML mode to an AI/ML mode, or switch from an AI/ML mode to a non-AI/ML mode, or switch from a current operation mode to a new operation mode.
2 . The user device, UE, of claim 1 , wherein the UE is configured or preconfigured with a plurality of AI/ML models of different complexity for performing a certain operation, and dependent on the one or more criteria, the UE is to switch from the first AI/ML model to the second AI/ML model for performing the certain operation, the second AI/ML model having a complexity lower or higher than the first AI/ML model.
3 . The user device, UE, of claim 1 , wherein the UE is configured or preconfigured with a plurality of AI/ML models to be executed in parallel for performing one or more certain operations, and in case the UE determines that computational capacities of the UE are not enough for operating the plurality of AI/ML models in parallel, the UE is to deactivate one or more of the plurality of AI/ML models.
4 . The user device, UE, of claim 3 , wherein the UE is to deactivate the one or more of the plurality of AI/ML models according to an order of deactivation that is determined by the UE or that may (pre-) configured, e.g., based on priorities.
5 . A user device, UE, of a wireless communication network, the wireless communication network using one or more Artificial Intelligence/Machine Learning, AI/ML, models for one or more use cases, wherein the UE is configured or preconfigured with a plurality of AI/ML models for performing one or more certain operations, wherein the UE comprises an AI/ML model processing circuitry, the AI/ML model processing circuitry having one or more constraints allowing executing only a certain number of the plurality of AI/ML models.
6 . The user device, UE, of claim 5 , wherein the UE is to map the processing of the plurality of AI/ML models to the AI/ML model processing circuitry taking into consideration the constraints of the AI/ML model processing circuitry and/or input received from the wireless communication network.
7 . The user device, UE, of claim 5 , wherein the AI/ML model processing circuitry constraints comprise: the AI/ML model processing circuitry of UE comprises only one AI/ML accelerator, the AI/ML model processing circuitry of the UE comprises two or more AI/ML accelerators, wherein the AL/ML models are mapped to the two or more AI/ML accelerators dependent on certain processing capabilities of the two or more AI/ML accelerators, e.g., dependent on whether the two or more AI/ML accelerators comprise the same processing capabilities or different processing capabilities, e.g., in case of the AI/ML model processing circuitry comprises a high performance Tensor Processing Unit, TPU and low performance core, like a Graphical Processing Unit, GPU, or Central Processing Unit, CPU, a definition of a processing time, e.g., the processing time may comprise a loading of the one or more AI/ML models plus a processing of the one or more AI/ML models, a loading of the one or more AI/ML models plus a processing of the one or more AI/ML models plus an update of one or more AI/ML models.
8 . The user device, UE, of claim 5 , wherein, in case the UE performs the processing of more than one AI/ML models on only one processor, the UE is to signal to a network entity of the wireless network which algorithm to execute or that a longer processing time required to calculate functions of the AI/ML model.
9 . The user device, UE, of claim 5 , wherein the UE is to receive from a network entity of the wireless communication network a signaling indicating a preference which AI/ML model to compute first, or a list of priorities for the plurality of AI/ML models, e.g., which AI/ML model to compute first, second, third, . . . .
10 . The user device, UE, of claim 5 , wherein, in case the UE switches processing from a current AI/ML model to a new AI/ML model, the UE is to signal to a network entity of the wireless communication network a duration of a re-configuration.
11 . The user device, UE, of claim 5 , wherein the UE is to switch processing from a current AI/ML model to a new AI/ML model in response to a request from a network entity of the wireless communication network, and responsive to the request or responsive to a trigger, the UE is to send to the wireless communication network one or one of the following: a confirmation message indicating that a loading of the new AI/ML model is successfully completed, a conflict message indicating that a loading is not possible of the new AI/ML model, e.g., together with a possible fallback AI/ML model to be used or which could be configured, an update message indicting a duration of a calculation of the new AI/ML model and/or a calculation duration of an additional, e.g., old, AI/ML model, which may require additional processing time.
12 . The user device, UE, of claim 5 , wherein the UE is to signal to a network entity of the wireless communication network how much processing capabilities are required for which of the plurality of AI/ML models.
13 . The user device, UE, of claim 5 , wherein a network entity of the wireless communication network comprises one or more of the following: a further UE, Remote UE, Relay UE, a Radio Access Network, RAN, entity, like a gNB or Road Side Unit, RSU, a Core Network, CN, entity, like an Access and Mobility Function, AMF, or a Location Management Function, LMF.
14 . A wireless communication system, like a 3 rd Generation Partnership Project, 3GPP, system or a WiFI system, comprising the user device, UE, of claim 1 .
15 . The user device, UE, of claim 1 , or the wireless communication network, wherein the UE comprises one or more of the following: a power-limited UE, or a hand-held UE, like a UE used by a pedestrian, and referred to as a Vulnerable Road User, VRU, or a Pedestrian UE, P-UE, or an on-body or hand-held UE used by public safety personnel and first responders, and referred to as Public safety UE, PS-UE, or an IoT UE, e.g., a sensor, an actuator or a UE provided in a campus network to carry out repetitive tasks and requiring input from a gateway node at periodic intervals, or a mobile terminal, or a stationary terminal, or a cellular IoT-UE, or a SL UE, or a vehicular UE, or a vehicular group leader UE, GL-UE, or a scheduling UE, S-UE, or an IoT or narrowband IoT, NB-IoT, device, or a ground based vehicle, or an aerial vehicle, or a drone, or a moving base station, or road side unit, RSU, or a building, or any other item or device provided with network connectivity enabling the item/device to communicate using the wireless communication network, e.g., a sensor or actuator, or any other item or device provided with network connectivity enabling the item/device to communicate using a sidelink the wireless communication network, e.g., a sensor or actuator, or a Wi-Fi device, station, access point, node or mesh node, or mesh point, or Mesh AP, or any sidelink capable network entity, and wherein the network entity of the wireless communication system comprises one or more of the following: a base station, like a macro cell base station, or a small cell base station, or a central unit of a base station, or a distributed unit of a base station, or an Integrated Access and Backhaul, IAB, node, or a Wi-Fi device such as an access point or mesh node a road side unit, RSU, a UE, like a SL UE, or a group leader UE, GL-UE, or a relay UE, a remote radio head, a core network entity, like an Access and Mobility Management Function, AMF, or a Service Management Function, SMF, or a mobile edge computing, MEC, entity, a network slice as in the NR or 5G core context, any transmission/reception point, TRP, enabling an item or a device to communicate using the wireless communication network, the item or device being provided with network connectivity to communicate using the wireless communication network.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation of copending International Application No. PCT/EP2024/055214, filed Feb. 29, 2024, which is incorporated herein by reference in its entirety, and additionally claims priority from European Application No. EP 23167001.9, filed Apr. 6, 2023, which is also incorporated herein by reference in its entirety. Embodiments of the present application relate to the field of wireless communication, and more specifically, to wireless communication using model related to the communication such as models on the physical layer-PHY. Some embodiments relate to signaling in connection with such models and/or to the use or training of such models. BACKGROUND OF THE INVENTION FIG. 1 is a schematic representation of an example of a terrestrial wireless network 100 including, as is shown in FIG. 1(a), a core network 102 and one or more radio access networks RAN1, RAN2, . . . . RANN. FIG. 1(b) is a schematic representation of an example of a radio access network RANn that may include one or more base stations gNB1 to gNB5, each serving a specific area surrounding the base station schematically represented by respective cells 1061 to 1065. The base stations are provided to serve users within a cell. The term base station, BS, refers to a gNB in 5G networks, an eNB in UMTS/LTE/LTE-A/LTE-A Pro, or just a BS in other mobile communication standards. A user may be a stationary device or a mobile device. The wireless communication system may also be accessed by mobile or stationary IoT devices which connect to a base station or to a user. The mobile devices or the IoT devices may include physical devices, ground based vehicles, such as robots or cars, aerial vehicles, such as manned or unmanned aerial vehicles (UAVs), the latter also referred to as drones, buildings and other items or devices having embedded therein electronics, software, sensors, actuators, or the like as well as network connectivity that enables these devices to collect and exchange data across an existing network infrastructure. FIG. 1(b) shows an exemplary view of five cells, however, the RANn may include more or less such cells, and RANn may also include only one base station. FIG. 1(b) shows two users UE1 and UE2, also referred to as user equipment, UE, that are in cell 1062 and that are served by base station gNB2. Another user UE3 is shown in cell 1064 which is served by base station gNB4. The arrows 1081, 1082 and 1083 schematically represent uplink/downlink connections for transmitting data from a user UE1, UE2 and UE3 to the base stations gNB2, gNB4 or for transmitting data from the base stations gNB2, gNB4 to the users UE1, UE2, UE3. Further, FIG. 1(b) shows two IoT devices 1101 and 1102 in cell 1064, which may be stationary or mobile devices. The IoT device 1101 accesses the wireless communication system via the base station gNB4 to receive and transmit data as schematically represented by arrow 1121. The IoT device 1102 accesses the wireless communication system via the user UE3 as is schematically represented by arrow 1122. The respective base station gNB1 to gNB5 may be connected to the core network 102, e.g., via the S1 interface, via respective backhaul links 1141 to 1145, which are schematically represented in FIG. 1(b) by the arrows pointing to “core”. The core network 102 may be connected to one or more external networks. Further, some or all of the respective base station gNB1 to gNB5 may connected, e.g., via the S1 or X2 interface or the XN interface in NR, with each other via respective backhaul links 1161 to 1165, which are schematically represented in FIG. 1(b) by the arrows pointing to “gNBs”. For data transmission a physical resource grid may be used. The physical resource grid may comprise a set of resource elements to which various physical channels and physical signals are mapped. For example, the physical channels may include the physical downlink, uplink and sidelink shared channels (PDSCH, PUSCH, PSSCH) carrying user specific data, also referred to as downlink, uplink and sidelink payload data, the physical broadcast channel (PBCH) carrying for example a master information block (MIB), the physical downlink shared channel (PDSCH) carrying for example a system information block (SIB), the physical downlink, uplink and sidelink control channels (PDCCH, PUCCH, PSSCH) carrying for example the downlink control information (DCI), the uplink control information (UCI) and the sidelink control information (SCI). For the uplink, the physical channels, or more precisely the transport channels according to 3GPP, may further include the physical random access channel (PRACH or RACH) used by UEs for accessing the network once a UE is synchronized and has obtained the MIB and SIB. The physical signals may comprise reference signals or symbols (RS), synchronization signals and the like. The resource grid may comprise a frame or radio frame having a certain duration in the time do