Communication Method, Communication Apparatus, and Communication Device

    公开(公告)号:US20230163909A1

    公开(公告)日:2023-05-25

    申请号:US18156797

    申请日:2023-01-19

    CPC classification number: H04L5/0048 H04L47/624 H04W84/12

    Abstract: A communication method includes: generating an extremely high-throughput physical layer protocol data unit (EHT PPDU), the EHT PPDU comprises a legacy physical layer preamble and a new physical layer preamble, wherein the legacy physical layer preamble comprises a legacy short training field (L-STF), a legacy long training field (L-LTF), a legacy signal (L-SIG) field in turn, a first field of the new physical layer preamble is a repeat of a field in the legacy physical layer preamble and is modulated by binary phase shift keying, BPSK; and sending the PPDU.

    Method and Apparatus for Transmitting Physical Layer Protocol Data Unit

    公开(公告)号:US20230115766A1

    公开(公告)日:2023-04-13

    申请号:US18073381

    申请日:2022-12-01

    Abstract: Embodiments of this application provide a method and an apparatus for transmitting a physical layer protocol data unit, to design a short training field sequence for a larger channel bandwidth. The short training field sequence designed in this application has a smaller peak-to-average power ratio PAPR and better performance. The method includes: generating a physical layer protocol data unit PPDU that complies with the 802.11be standard, where the PPDU includes a short training field, and a quantity of subcarriers of a frequency domain sequence of the short training field is greater than 2048; and sending the PPDU on a target channel, where a bandwidth of the target channel is greater than or equal to 160 MHz.

    Traffic Anomaly Detection Method, and Model Training Method and Apparatus

    公开(公告)号:US20220166681A1

    公开(公告)日:2022-05-26

    申请号:US17669638

    申请日:2022-02-11

    Abstract: A traffic anomaly detection method includes obtaining a target time series including N elements; obtaining a target parameter of the target time series, where the target parameter includes at least one of a periodic factor or a jitter density, the periodic factor represents a wave-shaped change that is presented in the target time series and that is about a long-term trend, and the jitter density represents a deviation between an actual value and a target value of the target time series within a target time; determining, from a plurality of types based on the target parameter, a first type to which the target time series belongs, where each of the types corresponds to one parameter set, and the target parameter belongs to a parameter set corresponding to the first type; and detecting an anomaly of the target time series based on a first-type decision model corresponding to the first type.

Patent Agency Ranking