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Quantifying Interference in WiLD Networks using Topography Data and Realistic Antenna Patterns

  • Avoiding possible interference is a key aspect to maximize the performance in Wi-Fi based Long Distance networks. In this paper we quantify self-induced interference based on data derived from our testbed and match the findings against simulations. By enhancing current simulation models with two key elements we significantly reduce the deviation between testbed and simulation: the usage of detailed antenna patterns compared to the cone model and propagation modeling enhanced by license-free topography data. Based on the gathered data we discuss several possible optimization approaches such as physical separation of local radios, tuning the sensitivity of the transmitter and using centralized compared to distributed channel assignment algorithms. While our testbed is based on 5 GHz Wi-Fi, we briefly discuss the possible impact of our results to other frequency bands.

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Metadaten
Document Type:Conference Object
Language:English
Author:Michael Rademacher, Mathias Kretschmer, Karl Jonas
Parent Title (English):2019 IEEE Wireless Communications and Networking Conference (WCNC), 15-18 April 2019, Marrakesh, Morocco
Pagenumber:6
ISBN:978-1-5386-7646-2
URN:urn:nbn:de:hbz:1044-opus-46572
DOI:https://doi.org/10.1109/WCNC.2019.8885965
Publisher:IEEE
Publishing Institution:Hochschule Bonn-Rhein-Sieg
Date of first publication:2019/10/31
Tag:802.11; Directional antennas; Interference; Measurement; Simulation; Wi-Fi
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2019/11/06
Licence (Multiple languages):License LogoIn Copyright (Urheberrechtsschutz)