TY - CPAPER U1 - Konferenzveröffentlichung A1 - Rademacher, Michael A1 - Kretschmer, Mathias A1 - Jonas, Karl T1 - Quantifying Interference in WiLD Networks using Topography Data and Realistic Antenna Patterns T2 - 2019 IEEE Wireless Communications and Networking Conference (WCNC), 15-18 April 2019, Marrakesh, Morocco N2 - 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. KW - Interference KW - Directional antennas KW - 802.11 KW - Wi-Fi KW - Simulation KW - Measurement Y1 - 2019 UN - https://nbn-resolving.org/urn:nbn:de:hbz:1044-opus-46572 SN - 978-1-5386-7646-2 SB - 978-1-5386-7646-2 U6 - https://doi.org/10.1109/WCNC.2019.8885965 DO - https://doi.org/10.1109/WCNC.2019.8885965 SP - 6 S1 - 6 PB - IEEE ER -