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31.
公开(公告)号:US10542562B2
公开(公告)日:2020-01-21
申请号:US15971602
申请日:2018-05-04
Applicant: Samsung Electronics Co., Ltd
Inventor: Saidhiraj Amuru , Hyunil Yoo , Anshuman Nigam , Ji-Yun Seol , Taeyoung Kim
Abstract: The present disclosure is related to a 5th generation (5G) or pre-5G communication system for supporting a higher data rate than a 4th generation (4G) communication system such as long term evolution (LTE). According to various embodiments of the present disclosure, a method for operating a base station in a wireless communication system is provided. The method comprises: generating remaining minimum system information (RMSI) comprising random access channel (RACH) configuration, wherein the RACH configuration comprises an association between RACH resources and one of a synchronization signal (SS) block and channel state information reference signal (CSI-RS) resources; and transmitting, to a user equipment (UE), the RMSI.
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公开(公告)号:US20190277957A1
公开(公告)日:2019-09-12
申请号:US16270486
申请日:2019-02-07
Applicant: Samsung Electronics Co., Ltd.
Inventor: Vikram Chandrasekhar , Jianzhong Zhang , Saidhiraj Amuru , Yeqing Hu , Hao Chen
Abstract: An apparatus for performing a wireless communication includes a communication interface configured to measure uplink (UL) Sounding Reference Signals (SRSs) transmitted from a mobile client device, and at least one processor configured to buffer a number of uplink (UL) SRS measurements derived from UL SRS transmissions of the mobile client device, the number of UL SRS measurements exceeding a threshold, extract features from UL SRS measurements, obtain a machine learning (ML) classifier for determining a category to be used for estimating mobility associated with the mobile client device, and determine the category of the mobile client device by applying the extracted features to the ML classifier. Methods and apparatus extract the features of either a set of power spectrum density measurements or a set of pre-processed frequency domain real and imaginary portions of UL SRS measurements and feed the features to an AI classifier for UE speed estimation.
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