Early Collision Detection for Massive Random Access in Satellite-Based Internet of Things

Li Zhen, Yukun Zhang, Keping Yu, Neeraj Kumar, Ahmed Barnawi, Yong Bin Xie

Research output: Contribution to journalArticlepeer-review

Abstract

As a complementary solution for seamless and ubiq- uitous coverage, satellite communications will play crucial roles in future global Internet of Things (IoT). Focusing on enhancing access efficiency and resource utilization of massive machine- type devices (MTDs), we propose an efficient collision detection scheme at the first step of random access (RA) procedure for satellite-based IoT. By leveraging a single root Zadoff-Chu (ZC) sequence with an elaborate set of cyclic shift offsets to generate all the available preamble sequences, the proposed scheme can achieve rapid collision detection and load estimation in one- shot correlation operation, while having the robustness to the non-orthogonal interference. The preamble detection probability, collision detection probability, and load monitoring accuracy, are mathematically analyzed, and an optimal set of preamble selection probabilities is given to maximize the overall load monitoring accuracy. Simulation results validate the remarkable performance improvement of our scheme by compared to the state-of-the-art collision detection schemes.

Original languageEnglish
JournalIEEE Transactions on Vehicular Technology
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Collision avoidance
  • collision detection
  • Correlation
  • Indexes
  • Internet of Things
  • Internet of Things (IoT)
  • massive access
  • Monitoring
  • Satellite communication
  • Satellites
  • Uplink
  • Zadoff-Chu (ZC) sequence

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

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