A Meta Distribution-Based Fine-Grained Analysis for Contention-based WiFi Backscatter Networks

Document Type

Conference Proceeding

Publication Date

1-1-2024

Abstract

WiFi backscatter communication has gained many applications, but its performance characteristics remain to be analyzed. While existing research has investigated the success probability of backscatter tags in contention-based WiFi backscatter networks (CWBNs), it has focused solely on the first-order statistic of the signal-to-interference-plus-noise ratio (SINR). In this paper, we present a meta distribution-based fine-grained analysis that provides high-order statistics of SINR and characterizes the disparity among backscatter transmission links in CWBNs. Leveraging stochastic geometry, we, for the first time, derive mathematical expressions for the b-th moments of conditional success probability and its meta distribution. The extensive Monte-Carlo simulation results validate the accuracy of our proposed theoretical model and demonstrate its outstanding value to help us understand the overall performance of CWBNs.

Identifier

85213353482 (Scopus)

ISBN

[9798350365221]

Publication Title

ICNSC 2024 - 21st International Conference on Networking, Sensing and Control: Artificial Intelligence for the Next Industrial Revolution

External Full Text Location

https://doi.org/10.1109/ICNSC62968.2024.10760116

Grant

0093/2022/A2

Fund Ref

Fundo para o Desenvolvimento das Ciências e da Tecnologia

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