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    APPARATUS FOR ACQUIRING INFORMATION INDICATIVE OF MISMATCH CONNECTIONS
    112.
    发明公开
    APPARATUS FOR ACQUIRING INFORMATION INDICATIVE OF MISMATCH CONNECTIONS 审中-公开

    公开(公告)号：US20240125868A1

    公开(公告)日：2024-04-18

    申请号：US18473866

    申请日：2023-09-25

    Applicant: Nokia Solutions and Networks Oy

    Inventor： Yannic BRACHMANN

    IPC: G01R31/55

    CPC classification number: G01R31/55

    Abstract: An apparatus include a first circuit board, which has a detection circuit. The first circuit board has a first plurality of cable plugs, wherein each of the cable plugs has an array of electrical contacts such that a same multiwire cable type is physically and electrically pluggable to the different cable plugs of the first plurality. The detection circuit is configured to obtain information indicative of whether, at least, one of the cable plugs is connected by a multiwire cable of the multiwire cable type to a matched cable plug of a second plurality of cable plugs on a second circuit board. The detection circuit is configured to obtain the information by sensing a pattern of direct current signals across a first subset of the electrical contacts of the one of the cable plugs of the first circuit board.

    Digital Pre-Distortion Using Convolutional Neural Networks
    114.
    发明公开
    Digital Pre-Distortion Using Convolutional Neural Networks 审中-公开

    公开(公告)号：US20240119264A1

    公开(公告)日：2024-04-11

    申请号：US18553886

    申请日：2022-03-15

    Applicant: Nokia Solutions and Networks Oy

    Inventor： Trung Kien Vu ,  Fei HU ,  Xue Quan XIONG ,  Antti NEIJONEN ,  Jukka Petteri TOLONEN ,  Jarkko Johannes SAVOLAINEN ,  Ziming WANG

    IPC: G06N3/045 ,  G06N3/0464 ,  G06N3/048

    CPC classification number: G06N3/045 ,  G06N3/0464 ,  G06N3/048

    Abstract: This specification relates to an apparatus which stores a machine-learned model including a first neural network block including multiple convolutional neural network layers, a second neural network block including at least one dilated convolutional neural network layer, and a linear transformation block. The apparatus is configured to receive input data representing in-phase and quadrature signals of an input signal that is to be amplified by a power amplifier, to process the received input data using the first neural network block of the machine learned model to generate a first neural network block output, to process the received input data using the second neural network block of the machine learned model to generate a second neural network block output, and to combine, using the linear transformation block, the first neural network block output and the second neural network block output to generate a pre-distorted signal for amplification by the power amplifier.

    ANOMALY DETECTION USING LOGS
    115.
    发明公开
    ANOMALY DETECTION USING LOGS 审中-公开

    公开(公告)号：US20240118957A1

    公开(公告)日：2024-04-11

    申请号：US18465074

    申请日：2023-09-11

    Applicant: Nokia Solutions and Networks Oy

    Inventor： Péter SZILÁGYI ,  Gabor HORVATH ,  Attila KADAR

    IPC: G06F11/07

    CPC classification number: G06F11/0751 ,  G06F11/0769

    Abstract: Converting each log of a sequence of N logs into an identifier among K different identifiers to obtain a sequence of N identifiers;



    for each n between 0 and N:

    for each K identifier: counting occurrences of the identifier among the first n identifiers of the sequence to obtain a front frequency of the identifier for the respective n; and
    for each K identifier: counting occurrences of the identifier among the last N−n identifiers of the sequence to obtain a rear frequency of the identifier for the respective n;
    arranging front frequencies and rear frequencies in a count vector;
    inputting the count vector an autoencoder to obtain an output vector for the respective n;
    determining a difference between the output vector and the count vector;
    marking the sequence as anomalous if the difference between the output vector and the count vector is larger than a threshold.

    Data center management based on probing
    117.
    发明授权
    Data center management based on probing 有权

    公开(公告)号：US11949580B2

    公开(公告)日：2024-04-02

    申请号：US17550826

    申请日：2021-12-14

    Applicant: NOKIA SOLUTIONS AND NETWORKS OY

    Inventor： Jayant Kotalwar

    IPC: H04L43/12 ,  H04L41/12 ,  H04L45/64

    CPC classification number: H04L43/12 ,  H04L41/12 ,  H04L45/64

    Abstract: Various example embodiments for supporting data center management are presented herein. Various example embodiments for supporting data center management may be configured to support fabric service management for a data center fabric including a set of servers and a fabric network configured to support communications of the servers. Various example embodiments for supporting fabric service management within a data center may be configured to support a capability for configuring a fabric network of the data center fabric of the data center based on merging and unmerging of underlay and overlay configurations. Various example embodiments for supporting fabric service management within a data center may be configured to support a capability for debugging a fabric network of the data center fabric of the data center based on use of probes.

    METHOD AND APPARATUS FOR AN EQUALIZER BASED ON VITERBI ALGORITHM
    119.
    发明公开
    METHOD AND APPARATUS FOR AN EQUALIZER BASED ON VITERBI ALGORITHM 审中-公开

    公开(公告)号：US20240106536A1

    公开(公告)日：2024-03-28

    申请号：US18449409

    申请日：2023-08-14

    Applicant: Nokia Solutions and Networks Oy

    Inventor： Yannick LEFEVRE

    IPC: H04B10/2507 ,  H04B10/54 ,  H04L25/03 ,  H04Q11/00

    CPC classification number: H04B10/2507 ,  H04B10/54 ,  H04L25/03878 ,  H04Q11/0067

    Abstract: An apparatus including at least one processor configured to execute instructions and cause the apparatus to perform, obtaining for a first possible state (s) of a received sample at the current time step (k), log-likelihood ratio, Ilr, values Ilrold,min, Ilrold,max of a first transmitted bit (bj), wherein, the Ilr values Ilrold,min, Ilrold,max are respectively associated with a most likely state and a less likely state related to a received sample at the previous time step (k−1); determining based on path metrics and branch metrics corresponding to the received sample at the current time step (k); a first parameter (Q) related to a difference between likelihoods of the most likely state and the less likely state; updating magnitude of the Ilr value Ilrold,min at least based on the Ilr value Ilrold,min, the Ilr value Ilrold,max, and the first parameter, to obtain an updated Ilr value Ilrold,updated.

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