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

Li Zhen, Yukun Zhang, Keping Yu*, Neeraj Kumar, Ahmed Barnawi, Yongbin Xie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

59 Citations (Scopus)


As a complementary solution for seamless and ubiquitous 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 exhibit the remarkable performance improvement of our scheme in typical satellite line-of-sight (LOS) scenario, by compared to the state-of-the-art collision detection schemes.

Original languageEnglish
Article number9416799
Pages (from-to)5184-5189
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Issue number5
Publication statusPublished - 2021 May


  • Internet of Things (IoT)
  • Satellite communication
  • Zadoff-Chu (ZC) sequence
  • collision detection
  • massive access

ASJC Scopus subject areas

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


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