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Performance Study for Co-existing Wi-Fi and ZigBee Systems and Design of Interoperability Techniques

Wireless local area networks (WLANs) and wireless sensor networks (WSNs) technologies have been comprehensively developed and deployed during recent years. Since commercial WLAN and WSN products share the same free of license frequency band, the low power, low rate ZigBee based WSNs are vulnerable to the interference from Wi-Fi WLANs. Therefore, it is important to evaluate the performance of ZigBee WSNs that are subjected to interference generated by collocated Wi-Fi WLANs and to design effective counter-measuring techniques should performance improvement is needed. In this research, a versatile testbed for conducting various experiments is established and the ZigBee system’s performance with different clear channel assessment (CCA) modes and energy detection (ED) thresholds are evaluated through extensive experimental measurements in the testbed. It can be concluded from the results that CCA has significant impact on ZigBee’s performance. An existing theoretical analysis approach that is based on the collision time model between ZigBee and Wi-Fi packets is suitably modified to provide analytical evaluation means of the cases we examined. In order to mitigate the interference from the collocated Wi-Fi system, a novel and effective interference-aware adaptive CCA (IAACCA) scheme is proposed and implemented as firmware flashed into Crossbow motes. Experiments confirmed the ability of IAACCA to countermeasure effectively interference generated by Wi-Fi and thus improve the performance of ZigBee WSNs. Finally, a thorough statistical analysis is performed to understand the factors impacting the performance of ZigBee system and is used to further verify our experimental methods.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/23169
Date January 2012
CreatorsTang, Yong
ContributorsMakrakis, Dimitrios, Mouftah, Hussein
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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