OBTAINING MEASURED INFORMATION AND PREDICTED INFORMATION RELATED TO AI/ ML MODEL

    公开(公告)号:US20250056288A1

    公开(公告)日:2025-02-13

    申请号:US18784301

    申请日:2024-07-25

    Abstract: Example embodiments of the present disclosure relate to obtaining of measured information and predicted information related to an Artificial Intelligence (AI)/Machine Learning (ML) model. In an example method, a first apparatus performs, during a first time period, first one or more measurements to obtain first measured information related to the first time period. The first apparatus determines, based on the first measured information, predicted information related to a second time period which is after the first time period. The first apparatus performs, during the second time period, second one or more measurements to obtain second measured information related to the second time period. The first apparatus transmits, to a second apparatus, the second measured information and the predicted information. In this way, a test mechanism framework may evaluate the prediction accuracy for AI/ML based prediction use case.

    Exploration data for network optimization

    公开(公告)号:US12088475B2

    公开(公告)日:2024-09-10

    申请号:US17755137

    申请日:2019-10-23

    CPC classification number: H04L41/16 G06F18/217 H04L69/22

    Abstract: An example method, apparatus, and computer-readable storage medium are provided for exploration procedures for network optimization. In one example implementation, the method may include generating, by a first network element, exploration data, the exploration data being generated by the first network element for evaluating performance at a second network element; transmitting, by the first network element, the exploration data to the second network element; and receiving, by the first network element, exploration data feedback from the second network element, the exploration data feedback received from the second network element based on processing of the exploration data by the second network element. In another example implementation, the method may include receiving, by a second network element, exploration data from a first network element; generating, by the second network element, exploration data feedback, the exploration data feedback generated in response to and based on the exploration data received from the first network element; and transmitting, by the second network element, the exploration data feedback to the first network element.

    Flexible reference signal design
    15.
    发明授权

    公开(公告)号:US10756785B2

    公开(公告)日:2020-08-25

    申请号:US15280026

    申请日:2016-09-29

    Abstract: A radio network sub-tiles reference signals (RSs) within a set of resource elements (REs) such that each sub-tiled RS occupies less than a time and/or frequency and/or power extent of its respective RE. The set of REs are dispersed across both frequency bins and time slots according to a pre-defined grid; and transmitted. The user equipment (UE) uses that pre-defined grid to locate within that transmission the set of dispersed REs. The UE accumulates and combines at least one subset of the sub-tiled RSs and estimates therefrom a quality; then reports uplink an indication of that estimated quality. Examples of the RSs include channel state information RSs, beam RSs and beam refinement RSs. Advantages are particularly relevant for 5G new radio systems.

    Channel Estimation Using Machine Learning
    17.
    发明公开

    公开(公告)号:US20240056336A1

    公开(公告)日:2024-02-15

    申请号:US18267138

    申请日:2021-12-09

    CPC classification number: H04L25/0254 H04L25/0204

    Abstract: A method for performing multiple-input and multiple-output channel estimation includes: generating, using a first machine-learning model, an initial set of estimated channel information from a first input set of channel information, wherein the first input set of channel information corresponds to a first plurality of radio-frequency chains, and wherein the estimated set of channel information corresponds to the first plurality of radio-frequency chains and a second plurality of radio-frequency chains; generating, using a second machine-learning model, a set of estimated channel phases from the initial set of estimated channel information and a second input set of channel information, wherein the second set of input channel information corresponds to the second plurality of radio-frequency chains; and combining the initial set of estimated channel information and the set of estimated channel phases to generate an enhanced set of estimated channel information.

    Massive MIMO antenna array
    18.
    发明授权

    公开(公告)号:US11888553B2

    公开(公告)日:2024-01-30

    申请号:US17766864

    申请日:2019-10-18

    CPC classification number: H04B7/0426

    Abstract: Inter-alia, an apparatus is disclosed comprising: at least one power amplifier coupled to at least one radio frequency power storage device, wherein the at least one power amplifier is configured to supply power to the at least one radio frequency power storage device, wherein the at least one power amplifier provides power to be used to amplify one or more radio frequency signals; wherein the at least one radio frequency power storage device is configured to store the power of the at least one power amplifier for a certain time period; and one or more antenna elements coupled to the at least one radio frequency power storage device, wherein the at least one radio frequency power storage device is configured to output stored power to at least one of the one or more antenna elements, wherein the power is output variably dependent upon a power demand of a required radio frequency power and/or amplitude needed to transmit the one or more radio frequency signals, wherein the power demand represents a power demand of the at least one antenna element to which the power is to be output. It is further disclosed an according method, and system.

    EXPLORATION DATA FOR NETWORK OPTIMIZATION

    公开(公告)号:US20220360501A1

    公开(公告)日:2022-11-10

    申请号:US17755137

    申请日:2019-10-23

    Abstract: An example method, apparatus, and computer-readable storage medium are provided for exploration procedures for network optimization. In one example implementation, the method may include generating, by a first network element, exploration data, the exploration data being generated by the first network element for evaluating performance at a second network element; transmitting, by the first network element, the exploration data to the second network element; and receiving, by the first network element, exploration data feedback from the second network element, the exploration data feedback received from the second network element based on processing of the exploration data by the second network element. In another example implementation, the method may include receiving, by a second network element, exploration data from a first network element; generating, by the second network element, exploration data feedback, the exploration data feedback generated in response to and based on the exploration data received from the first network element; and transmitting, by the second network element, the exploration data feedback to the first network element.

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