Interference Mitigation in Coexisting WLANs
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Wired Local Area Network (WLAN) is a popular infrastructure today where it’s mostly used for indoor environments. WLAN is easy to install for different applications, it’s easy to configure and the cost is less than the Wired LAN infrastructure. The WLAN operates in the unlicensed, shared frequency bands where there are variety of signals such as microwave ovens, cordless telephones, Wireless Personal Area Networks(WPANs). The growing popularity of different wireless devices operating in the unlicensed band increases the level of mutual interference from one to another, and causes a reduced QoS for all of them.
The focus of this thesis is to investigate two WLANs that share the same frequency band. The two WLANs coexist in the same geographical area and therefore will interfere with each other. The task of this thesis is to investigate if adaptive antennas can improve the performance of coexisting WLANs and allow them, to share the same geographical area. The benefit of adaptive antennas compared with the omnidirectional antenna is that they concentrate the main energy on one certain direction or point. By doing so adaptive antennas are able to give the user or AP higher antenna gain and at the same time reduce the interference in other directions. The adaptive antennas have also a long range coverage compared with the omnidirectional, for the most cases it will lead to a improvement of the network but in this thesis will it have a negative influence through higher generated interference between the users.
The obtained results showed that the adaptive antenna models improved the networks QoS in terms of throughput and network separation at certain distances. Also showed that when the networks came very near each other the adaptive antenna models lost there advantage over the omnidirectional antenna.
Place, publisher, year, edition, pages
2005. , 45 p.
TRITA-S3-RST, ISSN 1400-9137 ; 0517
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-28544OAI: oai:DiVA.org:kth-28544DiVA: diva2:387961
Slimane, Ben, Associate Professor