Error detection system
    221.
    发明授权
    Error detection system 失效
    错误检测系统

    公开(公告)号:US5321705A

    公开(公告)日:1994-06-14

    申请号:US860639

    申请日:1992-03-30

    Abstract: An error detection system for a discrete receiver. Sequences of bits together forming frames of information comprise the signal received by the discrete receiver. The signal is decoded by a convolutional decoder and is re-encoded by an encoder. Successive portions of nonoverlapping sets of adjacently positioned bits of the re-encoded signal formed by the encoder are compared with corresponding bits of a signal representative of the signal received by the receiver. When excessive numbers of the successive portions of the signals which are compared include bit dissimilarities, a bad frame indication is generated.

    Abstract translation: 用于离散接收机的错误检测系统。 一起形成信息帧的位序列包括由离散接收机接收的信号。 信号由卷积解码器解码,并由编码器重新编码。 将由编码器形成的重编码信号的相邻定位位的不重叠组的连续部分与表示由接收机接收的信号的信号的相应位进行比较。 当被比较的信号的连续部分的过多数量包括比特不相似时,产生坏帧指示。

    Anti-fraud control system, monitoring device, and anti-fraud control method

    公开(公告)号:US11909748B2

    公开(公告)日:2024-02-20

    申请号:US17224883

    申请日:2021-04-07

    CPC classification number: H04L63/1416 H04L1/201 H04L12/44

    Abstract: In an anti-fraud control system, a first error monitoring device includes a first frame transmitting and receiving unit that receives a frame flowing on the on-board network; and a first error detector that causes transmission of an error notification frame for notifying of an occurrence of an error in the frame when detecting the occurrence of the error in the frame received by the first frame transmitting and receiving unit. Each of second error monitoring devices includes: a second frame transmitting and receiving unit that receives the error notification frame; and a second error detector that regards, as a frame to be invalidated, the frame subjected to the error and included in the received error notification frame, and shifts the second error monitoring device to an invalidation mode for invalidating reception of subsequent frames, if no error is detected in an own branch with respect to the frame.

    Artificial intelligence for fault localization and mitigation in 5G/6G

    公开(公告)号:US11784764B2

    公开(公告)日:2023-10-10

    申请号:US18309844

    申请日:2023-05-01

    CPC classification number: H04L1/201 H04L1/206

    Abstract: A key requirement for 5G and 6G networking is reliability. Message faults are inevitable, and therefore procedures are needed to identify each fault location in a message and, if possible, to rectify it. Disclosed herein are artificial intelligence AI models and procedures for mitigating faults in wireless messages by (a) evaluating the signal quality of each message element according to waveform features and modulation deviations, (b) evaluating the fault probability of each message element by seeking correlations, which may be subtle, among the various waveform measurements including polarization and frequency offset, and (c) correcting the faults according to the message type, apparent format, intent or meaning, typical previous messages of a similar type, correlations of bit patterns and symbol sequences, error-detection codes if present, and other content-based indicators uncovered during model development. Automatic, real-time fault localization and correction may save substantial time and resources while substantially enhancing messaging reliability.

    Artificial Intelligence for Fault Localization and Mitigation in 5G/6G

    公开(公告)号:US20230275710A1

    公开(公告)日:2023-08-31

    申请号:US18309844

    申请日:2023-05-01

    CPC classification number: H04L1/201 H04L1/206

    Abstract: A key requirement for 5G and 6G networking is reliability. Message faults are inevitable, and therefore procedures are needed to identify each fault location in a message and, if possible, to rectify it. Disclosed herein are artificial intelligence AI models and procedures for mitigating faults in wireless messages by (a) evaluating the signal quality of each message element according to waveform features and modulation deviations, (b) evaluating the fault probability of each message element by seeking correlations, which may be subtle, among the various waveform measurements including polarization and frequency offset, and (c) correcting the faults according to the message type, apparent format, intent or meaning, typical previous messages of a similar type, correlations of bit patterns and symbol sequences, error-detection codes if present, and other content-based indicators uncovered during model development. Automatic, real-time fault localization and correction may save substantial time and resources while substantially enhancing messaging reliability.

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