RUcore Resource Object
RUcore Resource Object
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TitleMulti-radio interference diagnosis in unlicensed bands
using passive monitoring
NameBaid, Akash (author), Raychaudhuri, Dipankar (chair), Yates, Roy D (internal member), Mandayam, Narayan (internal member), Rutgers University, Graduate School - New Brunswick,
Degree Date2011-05
Date Created2011
SubjectElectrical and Computer Engineering,
Wireless communication systems,
Signal integrity (Electronics),
Radio--Interference
DescriptionThe increasing density and data rate of unlicensed band wireless devices has led to significant inter- and intra-radio interference problems. Multiple competing standards such as the IEEE 802.11b/g, Bluetooth and ZigBee, all of which operate in the 2.4 GHz ISM band, can interfere with each other when used in typical indoor environments, potentially causing significant performance degradation. This thesis aims to characterize different types of heterogeneous interference in the 2.4 GHz unlicensed band and develop techniques to diagnose interference related problems using passive monitoring. The first
part of the thesis presents detailed experimental results (using the ORBIT radio grid testbed) to quantify the effects of such interference in representative small office and home (SOHO) environment. In particular, different topologies, traffic loads and number
of interfering devices are emulated to show the impact of multi-radio interference and to characterize each kind of interference. The second part of the thesis describes
a cross-layer, multi-radio interference diagnosis framework (called “spectrum MRI”) which aims to classify and diagnose multi-radio interference problems using heuristic and model-based methods. Validation experiments show that broad auto-classification of multi-radio interference in terms of congestion, slow links, inter AP interference and
Bluetooth interference is possible using heuristic algorithms and passive monitoring.
part of the thesis presents detailed experimental results (using the ORBIT radio grid testbed) to quantify the effects of such interference in representative small office and home (SOHO) environment. In particular, different topologies, traffic loads and number
of interfering devices are emulated to show the impact of multi-radio interference and to characterize each kind of interference. The second part of the thesis describes
a cross-layer, multi-radio interference diagnosis framework (called “spectrum MRI”) which aims to classify and diagnose multi-radio interference problems using heuristic and model-based methods. Validation experiments show that broad auto-classification of multi-radio interference in terms of congestion, slow links, inter AP interference and
Bluetooth interference is possible using heuristic algorithms and passive monitoring.
NoteM.S.
NoteIncludes bibliographical references
Noteby Akash Baid
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000060983
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.