ADAPTING SEARCH, MEASUREMENT, AND LOOP TRACKING PERIODICITIES IN NEW RADIO COMMUNICATIONS

    公开(公告)号:US20220070707A1

    公开(公告)日:2022-03-03

    申请号:US17348635

    申请日:2021-06-15

    Abstract: Certain aspects of the present disclosure provide techniques for adapting search, measurement, and loop tracking periodicities in new radio communications. A method that may be performed by a user equipment (UE) includes determining, based on one or more parameters, a first periodicity to perform a search to detect one or more component carriers (CCs), cells, beams, or a combination thereof; a second periodicity to perform measurement of one or more cells, beams, or both in one more detected CCs; and a third periodicity to perform loop tracking to monitor a downlink serving quality, an uplink serving beam quality, or both of a cell. The method may further includes performing the search at the determined first periodicity, measurement at the determined second periodicity, and loop tracking at the determined third periodicity.

    Autonomous Beam Switching
    2.
    发明申请

    公开(公告)号:US20210337398A1

    公开(公告)日:2021-10-28

    申请号:US17242229

    申请日:2021-04-27

    Abstract: Various embodiments include methods for autonomous beam switching by a wireless device. A processor of the wireless device may measure signal parameters of signals received from a first synchronization signal block (SSB) beam of a base station monitored by the wireless device and other SSB beams of the base station, determine whether a difference in measured signal parameters of signals received from the first SSB beam and another SSB beam of the base station satisfies a signal quality difference threshold, and autonomously switching to the second SSB beam as the serving beam in response to determining that the difference in the measured signal parameters of signals received from the first SSB beam and a second SSB beam satisfies the signal quality difference threshold. The signal quality difference threshold may be listed in a table in memory or determined via machine learning.

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