Impact of clustering in indoor MIMO propagation using a hybrid channel model

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dc.contributor.author Tang, Z
dc.contributor.author Mohan, AS
dc.date.accessioned 2009-12-21T02:32:18Z
dc.date.issued 2005-07-11
dc.identifier.citation Eurasip Journal on Applied Signal Processing, 2005, 2005 (11), pp. 1698 - 1711
dc.identifier.issn 1110-8657
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/4225
dc.description.abstract The clustering of propagating signals in indoor environments can influence the performance of multiple-input multiple-output (MIMO) systems that employ multiple-element antennas at the transmitter and receiver. In order to clarify the effect of clustering propagation on the performance of indoor MIMO systems, we propose a simple and efficient indoor MIMO channel model. The proposed model, which is validated with on-site measurements, combines the statistical characteristics of signal clusters with deterministic ray tracing approach. Using the proposed model, the effect of signal clusters and the presence of the line-of-sight component in indoor Ricean channels are studied. Simulation results on channel efficiency and the angular sensitivity for different antenna array topologies inside a specified indoor scenario are also provided. Our investigations confirm that the clustering of signals significantly affects the spatial correlation, and hence, the achievable indoor MIMO capacity. © 2005 Hindawi Publishing Corporation.
dc.language eng
dc.relation.isbasedon 10.1155/ASP.2005.1698
dc.title Impact of clustering in indoor MIMO propagation using a hybrid channel model
dc.type Journal Article
dc.parent Eurasip Journal on Applied Signal Processing
dc.journal.volume 11
dc.journal.volume 2005
dc.journal.number 11 en_US
dc.publocation Sylvania, USA en_US
dc.identifier.startpage 1698 en_US
dc.identifier.endpage 1711 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 920438
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.custom 0.583 en_US
dc.description.keywords angle sensitivity; channel efficiency; indoor propagation; signal clusters; MIMO; Ricean K factor; ray tracing en_US
dc.description.keywords Angle sensitivity
dc.description.keywords Channel efficiency
dc.description.keywords Indoor propagation
dc.description.keywords MIMO
dc.description.keywords Ray tracing
dc.description.keywords Ricean K factor
dc.description.keywords Signal clusters
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
pubs.organisational-group /University of Technology Sydney/Strength - Health Technologies
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)


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