Spectrum Utilization and Congestion of IEEE 802.11 Networks in the 2.4 GHz ISM Band

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Bloem van, Jan-Willem and Schiphorst, Roel and Kluwer, Taco and Slump, Cornelis H. (2012) Spectrum Utilization and Congestion of IEEE 802.11 Networks in the 2.4 GHz ISM Band. Journal of Green Engineering, 2 (4). pp. 401-430. ISSN 1904-4720

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Abstract:Wi-Fi technology, plays a major role in society thanks to its widespread availability, ease of use and low cost. To assure its long term viability in terms of capacity and ability to share the spectrum efficiently, it is of paramount to study the spectrum utilization and congestion mechanisms in live environments. In this paper the service level in the 2.4 GHz ISM band is investigated with focus on todays IEEE 802.11 WLAN systems with support for the 802.11e extension. Here service level means the overall Quality of Service (QoS), i.e. can all devices fulfill their communication needs? A crosslayer approach is used, since the service level can be measured at several levels of the protocol stack. The focus is on monitoring at both the Physical (PHY) and the Medium Access Control (MAC) link layer simultaneously by performing respectively power measurements with a spectrum analyzer to assess spectrum utilization and packet sniffing to measure the congestion. Compared to traditional QoS analysis in 802.11 networks, packet sniffing allows to study the occurring congestion mechanisms more thoroughly. The monitoring is applied for the following two cases. First the influence of interference between WLAN networks sharing the same radio channel is investigated in a controlled environment. It turns out that retry rate, Clear-ToSend (CTS), Request-To-Send (RTS) and (Block) Acknowledgment (ACK) frames can be used to identify congestion, whereas the spectrum analyzer is employed to identify the source of interference. Secondly, live measurements are performed at three locations to identify this type of interference in real-live situations. Results show inefficient use of the wireless medium in certain scenarios, due to a large portion of management and control frames compared to data content frames (i.e. only 21% of the frames is identified as data frames).
Item Type:Article
Copyright:© 2012 The Author(s)
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/81459
Official URL:http://riverpublishers.com/journal/journal_articles/download_file.php?file=RP_Journal_1904-4720 _245.pdf
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