LOW COMPLEXITY ML AUGMENTED ROBUST CHANNEL ESTIMATION

    公开(公告)号:US20250158850A1

    公开(公告)日:2025-05-15

    申请号:US18930930

    申请日:2024-10-29

    Abstract: A method includes acquiring, by a processor of an electronic device, information associated with channel and noise covariances. The method includes determining one or more time-domain rectangular filters based on the information associated with the channel and noise covariances. The method includes generating one or more convolutional kernels based on the one or more rectangular filters applied to the channel and noise covariances in a time-domain. The method includes generating a codebook based on the one or more convolutional kernels, the codebook comprising N codewords. Further, the method can include establishing a communication link to a gNB configured to: receive a reference signal from a user equipment; receive the codebook; calculate channel statistics using a low complexity algorithm; execute a decision tree classifier to select a codeword from the codebook stored in memory of the gNB; and apply the selected codeword as convolution kernel for channel estimation.

    INTELLIGENT PROXIMITY SYSTEM
    2.
    发明申请

    公开(公告)号:US20250071508A1

    公开(公告)日:2025-02-27

    申请号:US18614620

    申请日:2024-03-22

    Abstract: An electronic device includes a transceiver configured to receive information related to an action request or rule. The electronic device further includes a processor operatively coupled to the transceiver. The processor is configured to determine that the action is location based, and identify a zone within which the electronic device is located. The identification of the zone is based on at least one of a first reception by the transceiver of at least one signal indicative of a location of the electronic device, and a second reception by the transceiver of at least one response to a transmission of a signal indicative of a location of the electronic device. The processor is further configured to trigger an action based on the action request or rule and the identified zone.

    SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE (AI) DRIVEN VOICE OVER LONG-TERM EVOLUTION (VoLTE) ANALYTICS

    公开(公告)号:US20220210682A1

    公开(公告)日:2022-06-30

    申请号:US17547002

    申请日:2021-12-09

    Abstract: A network management apparatus of a wireless network includes a network interface, a processor, and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to receive, via the network interface, first data comprising values of key performance indicators (KPIs) obtained from elements of the wireless network for a first time period, receive, via the network interface, second data comprising values of key quality indicators (KQIs) for the first time period, wherein the KQIs comprise metrics of end-user quality of service (QoS) of the wireless network, and perform supervised learning to train an artificial intelligence (AI) model based on the first and second data, wherein features of the AI model are based on KPIs available from elements of the wireless network, and outputs of the AI model comprise values of one or more KQIs.

    CHANNEL STATE INFORMATION UPSAMPLING IN WIRELESS COMMUNICATION NETWORK

    公开(公告)号:US20250088228A1

    公开(公告)日:2025-03-13

    申请号:US18822038

    申请日:2024-08-30

    Abstract: Methods and apparatuses for an operation for a channel state information upsampling in a wireless communication system. A method of BS includes: receiving, from a UE, feedback information including at least one SB level precoder; identifying, based on the at least one SB level precoder, a mapping function to perform an up-sampling operation; performing, based on the mapping function, the up-sampling operation to the at least one SB level precoder; and identifying, based on the up-sampling operation, at least one RB level precoder from the at least one SB level precoder for a precoder gain of the BS.

    METHOD AND APPARATUS FOR RELATIONSHIP INFORMATION BASED TRAFFIC PREDICTION

    公开(公告)号:US20250008403A1

    公开(公告)日:2025-01-02

    申请号:US18345549

    申请日:2023-06-30

    Abstract: A method includes generating relationship information representing spatial relationships between network elements in a wireless communication network. The method also includes dividing the relationship information into multiple communities of network elements, wherein network elements within each community have a higher correlation than network elements in different communities. The method also includes identifying, for a target network element, one or more community level key network elements and one or more local key network elements in the relationship information. The method also includes predicting traffic at the target network element using a temporal-spatial algorithm, wherein the temporal-spatial algorithm predicts the traffic based on temporal features derived from historical data and spatial features derived from the one or more community level key network elements and the one or more local key network elements.

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