Interference Model Similarity Index and Its Applications to mmWave Networks: Extended version
Hossein Shokri-Ghadikolaei, Carlo Fischione, Eytan Modiano

TL;DR
This paper introduces a new index to evaluate the accuracy of interference models in wireless networks, especially mmWave, enabling simplified yet effective modeling for network analysis and design.
Contribution
It proposes a novel interference model similarity index applicable across various scenarios, facilitating model selection and simplification in wireless network analysis.
Findings
Simple models are accurate in highly directional mmWave scenarios with obstructions.
Complex models are necessary for omnidirectional antenna settings.
The index aids in developing simplified interference models for mmWave networks.
Abstract
In wireless communication networks, interference models are routinely used for tasks such as performance analysis, optimization, and protocol design. These tasks are heavily affected by the accuracy and tractability of the interference models. Yet, quantifying the accuracy of these models remains a major challenge. In this paper, we propose a new index for assessing the accuracy of any interference model under any network scenario. Specifically, it is based on a new index that quantifies the ability of any interference model in correctly predicting harmful interference events, that is, link outages. We consider a specific wireless scenario of both conventional sub-6~GHz and millimeter-wave (mmWave) networks and demonstrate how our index yields insights into the possibility of simplifying the set of dominant interferers, replacing a Nakagami or Rayleigh random fading by an equivalent…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Advanced MIMO Systems Optimization · Antenna Design and Analysis
