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Experimental analysis of the interference impact of Wi-Fi on ZigBee using cognitive radio

Author: Harvy Younan
Publisher: [Long Beach, California] : California State University, Long Beach, 2011.
Dissertation: M.S. California State University, Long Beach 2011
Series: California State University, Long Beach.; Master's thesis collection, Dept. of Electrical Engineering.
Edition/Format:   Thesis/dissertation : Document : Thesis/dissertation   Computer File : English
Summary:
Abstract: The increase of ZigBee popularity and usage in different Home Area Networks (HAN) exert a new challenge for operating ZigBee in an environment that is already using Wi-Fi. Sharing the spectrum between these two wireless technologies affect the functionality of ZigBee as it may cause a high packet error rate (PER) and major drop in the throughput. In this thesis we studied the effect of Wi-Fi interference  Read more...
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Genre/Form: Academic theses
Material Type: Document, Thesis/dissertation, Internet resource
Document Type: Book, Computer File, Internet Resource
All Authors / Contributors: Harvy Younan
ISBN: 9781267309129 1267309121
OCLC Number: 1061314400
Description: 2, xi, 89 leaves : color illustrations, charts
Series Title: California State University, Long Beach.; Master's thesis collection, Dept. of Electrical Engineering.
Responsibility: by Harvy Younan.

Abstract:

Abstract: The increase of ZigBee popularity and usage in different Home Area Networks (HAN) exert a new challenge for operating ZigBee in an environment that is already using Wi-Fi. Sharing the spectrum between these two wireless technologies affect the functionality of ZigBee as it may cause a high packet error rate (PER) and major drop in the throughput. In this thesis we studied the effect of Wi-Fi interference on ZigBee channels by using the Cognitive Radio as Spectrum Analyzer and computed the packet error rate of each of the ZigBee channels. The results that we have obtained contradict the previous analytical and simulation results in which the effect of Wi-Fi on ZigBee has been studied. In the previous works, the authors assumed that the in-band interference signal of the Wi-Fi is a limited Adaptive White Gaussian Noise (AWGN). Therefore, their results were based only on the interference level on each of the ZigBee channels. In this work, we prove that the aforementioned assumption does not hold in all cases. Therefore, the obtained results are based on the interference level and distribution of the interference on each of the ZigBee channels.

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