SERVER AND AGENT FOR REPORTING OF COMPUTATIONAL RESULTS DURING AN ITERATIVE LEARNING PROCESS

    公开(公告)号:US20240303500A1

    公开(公告)日:2024-09-12

    申请号:US18573124

    申请日:2021-07-06

    IPC分类号: G06N3/092 G06N3/0455

    CPC分类号: G06N3/092 G06N3/0455

    摘要: There is provided mechanisms for configuring agent entities with a reporting schedule for reporting computational results during an iterative learning process. A method is performed by a server entity. The method comprises configuring the agent entities with a computational task and a reporting schedule. The reporting schedule defines an order according to which the agent entities are to report computational results of the computational task. The agent entities are configured to, per each iteration of the learning process, base their computation of the computational task on any computational result of the computational task received from any other of the agent entities prior to when the agent entities themselves are scheduled to report their own computational results for that iteration. The method comprises performing the iterative learning process with the agent entities according to the reporting schedule and until a termination criterion is met.

    Compression and decompression of delay profile

    公开(公告)号:US12034461B2

    公开(公告)日:2024-07-09

    申请号:US17795333

    申请日:2020-03-06

    摘要: In a first method, a wireless device estimates a delay profile of a channel impulse response, CIR, for a channel between a network node and the wireless device, compresses the delay profile using a compression function, and transmits the compressed delay profile. The compression function includes a first function and a quantizer. The first function is configured to receive input data and reduce a dimension of the input data. In a second method, a network node receives a compressed delay profile of CIR for a channel between a network node and a wireless device, decompresses the compressed delay profile using a decompression function, and estimates a position of the wireless device based on at least the decompressed delay profile. The decompression function includes a first function which is configured to receive input data and provide output data in a higher dimensional space than the input data.

    MANAGING A WIRELESS DEVICE THAT IS OPERABLE TO CONNECT TO A COMMUNICATION NETWORK

    公开(公告)号:US20230276263A1

    公开(公告)日:2023-08-31

    申请号:US18015978

    申请日:2021-07-09

    IPC分类号: H04W24/02 H04W8/22 H04L41/16

    CPC分类号: H04W24/02 H04L41/16 H04W8/22

    摘要: A method is disclosed for managing a wireless device that is operable to connect to a communication network. The communication network comprises a RAN, and the wireless device has available for execution multiple ML models each operable to provide an output, on the basis of which at least one RAN operation performed by the wireless device may be configured. The method, performed by the wireless device, comprises determining which of said available ML models should be stored in the wireless device. The method further comprises, in response to determining that at least one of said available ML models should be stored in the wireless device, storing said at least one of said available ML models, and, in response to determining that at least one of said available ML models should not be stored in the wireless device, deleting said at least one of said available ML models.

    Measurement Reporting in a Wireless Communication Network

    公开(公告)号:US20230143060A1

    公开(公告)日:2023-05-11

    申请号:US17913506

    申请日:2021-03-31

    IPC分类号: H04W24/10

    CPC分类号: H04W24/10

    摘要: A method performed by a wireless device (12) comprises receiving (500), from a network node (18) in a wireless communication network (10), signaling (20) that indicates one or more report triggering measurement objects (22) and one or more report content measurement objects (24). The one or more report triggering measurement objects (22) are one or more objects of measurements whose results (22R) are to be evaluated by the wireless device (12) for determining whether to log or send a measurement report (16). The one or more report content measurement objects (24) are one or more objects of measurements whose results (22R) are to be reported by the measurement report (16). The signaling (20) is configurable to indicate at least one report content measurement object (24) that is different from each of the one or more report triggering measurement objects (22) indicated by the signaling (20).

    Inter-frequency search order
    7.
    发明授权

    公开(公告)号:US11490298B2

    公开(公告)日:2022-11-01

    申请号:US16644828

    申请日:2018-10-01

    IPC分类号: H04W36/00 H04W24/10

    摘要: A method (420) performed by a network node (102, 700, 800, 960a, 1320) for channel selection for inter-frequency handover. The method comprises generating (400) information usable by a user equipment (UE) (101, 500, 600, 910a, 1330) for determining a sequence of channels to be successively measured by the UE for availability for inter-frequency handover. The method comprises transmitting (410) the information to the UE. A method (320) performed by a wireless device for measuring channels available for inter-frequency handover. The method comprises determining (300) a channel order defining a sequence of channels to be successively measured for availability for inter-frequency handover. The method comprises performing (310) measurement of the channels according to the channel order.

    Network Controlled Machine Learning in User Equipment

    公开(公告)号:US20220321647A1

    公开(公告)日:2022-10-06

    申请号:US17218675

    申请日:2021-03-31

    摘要: Embodiments include methods for managed machine learning (ML) in a communication network, such as by one or more first network functions (NFs) of the communication network. Such methods include determining whether processing of an ML model in the communication network should be distributed to one or more user equipment (UEs) operating in the communication network, based on characteristics of the respective UEs. Such methods also include, based on determining that the processing of the ML model should be distributed to the one or more UEs, establishing trusted execution environments (TEEs) in the respective UEs and distributing the ML model for processing in the respective TEEs. Other embodiments include complementary methods for UEs, as well as UEs and NFs (or communication networks) configured to perform such methods.