English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper proposes a novel approach for computing the meta distribution ofthe signal-to-interference-plus-noise ratio (SINR) for the downlinktransmission in a wireless network with Rayleigh fading. The novel approachrelies on an approximation mix of exact and mean-field analysis of interference(dominant interferer-based approximation) to reduce the complexity of analysisand enhance tractability. In particular, the proposed approximation omits theneed to compute the first or the second moment of the SINR that is used in thebeta approximation typically adopted in the literature but requires ofcomputing the joint distance distributions. We first derive the proposedapproximation based on a Poisson point process (PPP) network with a standardpath-loss and Rayleigh fading and then illustrate its accuracy and operabilityin another four widely used point processes: Poisson bipolar network,Mat\'{e}rn cluster process (MCP), $K$-tier PPP and Poisson line Cox process(PLCP). Specifically, we obtain the SINR meta distribution for PLCP networksfor the first time. Even though the proposed approximation looks simple but itshows good matching in comparison to the popular beta approximation as well asthe Monte-Carlo simulations, which opens the door to adopting thisapproximation in more advanced network architectures.

A Dominant Interferer plus Mean Field-based Approximation for SINR Meta Distribution in Wireless Networks