Stochastic geometry based analysis for heterogeneous networks: a perspective on meta distribution

Xinlei Yu, Qimei Cui, Yuanjie Wang, Na Li, Xiaofeng Tao, Mikko Valkama

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
26 Downloads (Pure)

Abstract

The meta distribution as a new performance metric can provide much more fine-grained information about the individual link reliability, and is of great value for the analysis and design of the future cellular networks. In this paper, we investigate the stochastic geometry based analysis for heterogeneous networks from the perspective on the meta distribution. The comprehensive overview for the fundamental framework of the meta distribution is provided, which involves the concepts of the meta distribution and its related performance metric (e.g., mean local delay and spatial outage capacity) and the efficient calculation methods of the meta distribution. The insights of the meta distribution are also stated by the comparison with standard success probability. The various applications of the meta distribution to heterogeneous networks are summarized and categorized by different types of technologies. Furthermore, some open issues and future work are discussed to promote the development and application of the meta distribution.

Original languageEnglish
Article number223301
JournalScience China Information Sciences
Volume63
Issue number12
DOIs
Publication statusPublished - 1 Dec 2020
Publication typeA1 Journal article-refereed

Keywords

  • heterogeneous network
  • meta distribution
  • per-link reliability
  • stochastic geometry
  • success probability

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • General Computer Science

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