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SINR Model with Best Server Association for High Availability Studies of Wireless Networks

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David Oehmann, Ahmad Awada, Ingo Viering, Meryem Simsek, Gerhard P. Fettweis

Networking and Internet Architecture · Submitted 15 Oct 2015

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The SINR model is capable to describe all parts of the SINR distribution in detail, especially the left tail which is of interest for studies of high availability.

how it is stated · asserted 0.97 read the record →

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arXiv ID1510.04503 (version 2)
Pith IDUF3N37ZE, Pith's permanent record of this paper and its review
CitationAhmad Awada, David Oehmann, Gerhard P. Fettweis, Ingo Viering, Meryem Simsek. "SINR Model with Best Server Association for High Availability Studies of Wireless Networks." arXiv:1510.04503 (2015). https://pith.science/paper/UF3N37ZE
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,178 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.03 · randomized assignment 0.03 · states quantitative result 0.04 · compares with prior results 0.06 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

The signal-to-interference-and-noise ratio (SINR) is of key importance for the analysis and design of wireless networks. For addressing new requirements imposed on wireless communication, in particular high availability, a highly accurate modeling of the SINR is needed. We propose a stochastic model of the SINR distribution where shadow fading is characterized by random variables. Therein, the impact of shadow fading on the user association is incorporated by modification of the distributions involved. The SINR model is capable to describe all parts of the SINR distribution in detail, especially the left tail which is of interest for studies of high availability.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The signal-to-interference-and-noise ratio (SINR) is of key importance for the analysis and design of wireless networks. background 1.00 0.05 0.03 asserted 1.00
s1 For addressing new requirements imposed on wireless communication, in particular high availability, a highly accurate modeling of the SINR is needed. background 0.73 0.06 0.05 asserted 1.00
s2 We propose a stochastic model of the SINR distribution where shadow fading is characterized by random variables. contribution 0.56 0.94 0.13 asserted 0.99
s3 Therein, the impact of shadow fading on the user association is incorporated by modification of the distributions involved. method 0.95 0.83 0.09 asserted 1.00
s4 The SINR model is capable to describe all parts of the SINR distribution in detail, especially the left tail which is of interest for studies of high availability. contribution 0.54 0.87 0.46 asserted 0.97

What kind of paper the classifier reports this is: theoretical result 0.92 · evidence from proof or derivation 0.84.

What was examined, and what was not

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  • figures and tables
  • references and citing sentences
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  • P abstract
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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The signal-to-interference-and-noise ratio (SINR) is of key importance for the analysis and design of wireless networks. For addressing new requirements imposed on wireless communication, in particular high availability, a highly accurate modeling of the SINR is needed. We propose a stochastic model of the SINR distribution where shadow fading is characterized by random variables. Therein, the impact of shadow fading on the user association is incorporated by modification of the distributions involved. The SINR model is capable to describe all parts of the SINR distribution in detail, especially the left tail which is of interest for studies of high availability.

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