Meta Distribution of SIR in Ultra-Dense Networks with Bipartite Euclidean Matchings

Alexander P Kartun-Giles*, Kostas Koufos, Sunwoo Kim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


In this paper we study how a bipartite Euclidean matching can be used to investigate the reliability of communication in interference-limited ultra-dense networks. We do this by studying the corresponding statistics of the meta distribution of the signal-to-interference ratio in a near-optimally short Euclidean distance edge-weighted bipartite matching between two Poisson point processes. This gives the proportion of point processes which have a reliable link near the origin, or, due to ergodicity, the proportion of all links, in one randomly selected point pattern, which are reliable. The new matching idea effectively leads to variable link distances, a factor not typically incorporated in meta distribution studies. We ask how this effects its statistics, deriving the moments of the meta distribution, comparing with Monte Carlo simulations, and analysing the key differences which appear, particularly the effects of the significantly different link distance distribution.
Original languageEnglish
Title of host publicationIEEE International Conference Communications (ICC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
Publication statusAccepted/In press - 27 Jan 2020
EventIEEE International Conference on Communications - Dublin, Ireland
Duration: 7 Jun 202011 Jun 2020


ConferenceIEEE International Conference on Communications
Abbreviated titleIEEE ICC
Internet address


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