Nowadays, a vast majority of the Wi-Fi systems operates in the 2.4 GHz ISM band that becomes more and more crowded due to the growing usage of Wi-Fi. On top of that, a growing number of non Wi-Fi technologies become active in this band as well. In this thesis the focus is on spectrum sensing and detection techniques to enhance the coexistence with Wi-Fi systems.First, we investigate spectrum sensing for monitoring short-range wireless technologies. We show the value of using mobile spectrum monitoring equipment and results are presented concordantly. Additionally the impact of Automatic Gain Control (AGC), an essential building block in spectrum monitoring receivers, is investigated in order to enhance spectrum sensing performance. By doing so, techniques are developed to remove the AGC influences from the monitoring spectrum data. The results show that interference due to the AGC could lead to an overestimation of the actual spectrum usage by 60% in the ISM band.Secondly, the influence of interference on Wi-Fi systems has been investigated. This entails respectively interference due to non Wi-Fi technologies and interference due to overlapping Wi-Fi networks. For this purpose a methodology has been developed to assess spectrum utilization and to measure the congestion simultaneously. The obtained results show the inefficient use of the wireless medium due to a large amount of transmission overhead which may lead to only 21% of actual data in highly congested areas.Thirdly, the alternative use of Wi-Fi communication in the licensed TV-bands has been investigated to alleviate the congestion and interference issues in the ISM band. The operation of Wi-Fi systems in these bands is considered to be allowed under the condition of secondary use, i.e. avoiding interference to users with the primary rights (e.g. TV-broadcasting stations). For this purpose a novel collaborative sensing scheme with geolocation access to a central white-space database is presented.
|Award date||16 May 2013|
|Place of Publication||Enschede|
|Publication status||Published - 16 May 2013|
- Spectrum Sensing
- IEEE 802.11
- Cognitive Radio