RAPID: Contention Resolution-based Random Access using Context ID for IoT

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • Seoul National University
  • SK Telecom
  • Sejong University

Abstract

With the increasing number of Internet of Things (IoT) devices, Machine Type Communication (MTC) has become an important use case of the Fifth Generation (5G) communication systems. Since MTC devices are mostly disconnected from Base Station (BS) for power saving, random access procedure is required for devices to transmit data. If many devices try random access simultaneously, preamble collision problem occurs, thus causing latency increase. In an environment where delay-sensitive and delay-tolerant devices coexist, the contention-based random access procedure cannot satisfy latency requirements of delay-sensitive devices. Therefore, we propose RAPID, a novel random access procedure, which is completed through two message exchanges for the delay-sensitive devices. We also develop Access Pattern Analyzer (APA), which estimates traffic characteristics of MTC devices. When UEs, performing RAPID and contention-based random access, coexist, it is important to determine a value which is the number of preambles for RAPID to reduce random access load. Thus, we analyze random access load using a Markov chain model to obtain the optimal number of preambles for RAPID. Simulation results show RAPID achieves 99.999% reliability with 80.8% shorter uplink latency, and also decreases random access load by 30.5% compared with state-of-the-art techniques.

Details

Original languageEnglish
Article number8730509
Pages (from-to)7121-7135
Number of pages15
JournalIEEE Transactions on Vehicular Technology
Volume68
Issue number7
Early online date2019
Publication statusPublished - 1 Jul 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Uplink, 5G mobile communication, Load modeling, 3GPP, Internet of Things, Markov processes, Delays, 2-step random access, 5G, Internet of things, Markov chain model, and radio resource control state

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