Integrated 2–4 Step Random Access for Heterogeneous and Massive IoT Devices

IF 5.3 2区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Green Communications and Networking Pub Date : 2023-10-06 DOI:10.1109/TGCN.2023.3322539
Yijun Piao;Tae-Jin Lee
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Abstract

Since massive number of User Equipment (UE)s will cause more collisions and increase delay, improved Random Access (RA) methods have been researched and proposed. With the introduction of the new two step RA procedure in 3rd Generation Partnership Project (3GPP) Release 16, the average RA delay of UE could be further reduced. To further enhance two step RA in association with four step RA, we propose a new RA method that integrates four step RA and two step RA for heterogeneous IoT devices, so that UEs can perform two types of RA methods in parallel. With the proposed method, we aim to minimize the UE conflicts with the available RA resources, increasing the efficiency of RA and decreasing the average RA delay. We optimize the probability of two step RA in the proposed method and present algorithm to provide the optimal resource configuration and parameter settings in the RA procedure according to the RA status of UEs. A Markov chain model is formulated to analyze and confirm the effectiveness of the proposed RA method. As a result of extensive simulations, we present that the proposed RA method can enhance the property of the RA procedure for massive and heterogeneous devices access scenarios in 5G and 6G communications.
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为异构和大规模物联网设备集成 2-4 步随机存取功能
由于大量的用户设备(UE)会导致更多的碰撞并增加延迟,因此人们研究并提出了改进的随机接入(RA)方法。随着第三代合作伙伴计划(3GPP)第 16 版引入新的两步 RA 程序,UE 的平均 RA 时延可进一步降低。为了进一步加强两步 RA 与四步 RA 的结合,我们针对异构物联网设备提出了一种整合了四步 RA 和两步 RA 的新 RA 方法,使 UE 可以并行执行两种 RA 方法。通过所提出的方法,我们旨在最大限度地减少 UE 与可用 RA 资源的冲突,从而提高 RA 的效率并降低 RA 的平均延迟。我们优化了所提方法中两步 RA 的概率,并提出了一种算法,可根据 UE 的 RA 状态在 RA 过程中提供最优资源配置和参数设置。建立了马尔可夫链模型来分析和确认拟议 RA 方法的有效性。通过大量仿真,我们发现所提出的 RA 方法可以增强 5G 和 6G 通信中大规模和异构设备接入场景下 RA 程序的性能。
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来源期刊
IEEE Transactions on Green Communications and Networking
IEEE Transactions on Green Communications and Networking Computer Science-Computer Networks and Communications
CiteScore
9.30
自引率
6.20%
发文量
181
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