期刊
IEEE NETWORK
卷 35, 期 1, 页码 273-279出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.011.2000317
关键词
Payloads; Amplitude modulation; Uplink; Timing; 3GPP; OFDM; Discrete Fourier transforms
类别
资金
- Institute for Information & Communications Technology Promotion (IITP) - Korean government (MSIT) [2018-0-00815]
- Samsung Research in Samsung Electronics
- Academy of Finland [311654, 318927]
This article discusses the introduction of the Two-step Random Access Channel (2-step RACH) and the challenges associated with it in the 3GPP Release 16, focusing on how User Equipment (UE) performs self-uplink synchronization with the next-generation Node B to resolve preamble collisions.
The 3rd Generation Partnership Project (3GPP) finalized Release 15 specifications for the 5th Generation New Radio (5G NR) in June 2018. In Release 16, the 3GPP worked on not only technical improvements over the previous release but also the introduction of new features. One of the new features is the use of Two-step Random Access Channel (2-step RACH) that enhances 4-step random access with respect to radio resource control connection setup and resume procedures. In this article, we first look into details of 2-step random access defined in the 3GPP Release 16, and briefly introduce recent literature related to 2-step random access. Second, we present challenges of the above random access schemes. Among the challenges, we focus on how a User Equipment (UE) performs self-uplink synchronization with the next-generation Node B (gNB) to resolve preamble collisions, which occur when multiple UEs transmit the same preamble. Specifically, we propose a framework that helps the UE estimate the Timing Advance (TA) command using a deep neural network model and to determine the TA value. Finally, we evaluate the proposed framework in terms of the accuracy of TA command estimation, the inference time, and the battery consumption.
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