Propagation parameter estimation in MIMO systems

 |  Login

Show simple item record

dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Ribeiro, Cássio Barboza
dc.date.accessioned 2012-08-08T09:25:57Z
dc.date.available 2012-08-08T09:25:57Z
dc.date.issued 2008
dc.identifier.isbn 978-951-22-9303-2
dc.identifier.isbn 978-951-22-9302-5 (printed)
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/4432
dc.description.abstract Multiple antenna techniques are in the heart of modern and next-generation wireless communications systems, such as 3GPP Long-Term Evolution (LTE), IEEE 802.16e (WiMAX), and IMT-Advanced (IMT-A). Such techniques are considered for the high link capacity gains that are achievable from spatial multiplexing, and also for the system capacity, link reliability, and coverage benefits that are possible from spatial diversity, beamforming, and spatial division multiple access techniques. Accurate spatial channel models play a key role on the characterization of the propagation environment and determination of which techniques provide higher gains in a given scenario. Such models are also fundamental tools in network planning, link and system performance studies, and transceiver development. Realistic channel models are based on measurements. Hence, there is a need for techniques that extract the relevant information from huge amount of data. This may be achieved by estimating model parameters from the data. Most estimation algorithms are based on the assumption that the channel can be modeled as a combination of a finite number of specular, highly-concentrated paths, requiring estimation of a very large number of parameters. In this thesis, estimators are derived for the parameters of the concentrated propagation paths and the diffuse scattering component that are frequently observed in Multiple-Input Multiple-Output (MIMO) channel sounding measurements. Low complexity methods are derived for efficient computation of the estimates. The derived methods are based on a stochastic channel model, leading to a lower-dimensional parameter set that allow a reduction in computational complexity and improved statistical performance compared to methods found in the literature. Simulation results demonstrate that high quality estimates are obtained. The large sample performance of the estimators are studied by establishing the Cramér-Rao lower bound (CRLB) and comparing it to the variances of the estimates. The simulations show that the variances of the proposed estimation techniques attain the CRLB for relatively small sample size for most parameters, and no bias is observed. en
dc.format.extent Verkkokirja (919 KB, 102 s.)
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Teknillinen korkeakoulu en
dc.relation.haspart [Publication 1]: Cássio B. Ribeiro, Esa Ollila, and Visa Koivunen, 2004, Stochastic maximum likelihood method for propagation parameter estimation, in Proceedings of the 15th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2004), Barcelona, Spain, 5-8 September 2004, volume 3, pages 1839-1843. © 2004 IEEE. By permission. en
dc.relation.haspart [Publication 2]: Cássio B. Ribeiro, Esa Ollila, and Visa Koivunen, 2004, Cramér-Rao bound for angular propagation parameter estimation in MIMO systems, in Proceedings of the 38th Asilomar Conference on Signals, Systems, and Computers (ACSSC 2004), Pacific Grove, CA, USA, 7-10 November 2004, volume 2, pages 1785-1789. © 2004 IEEE. By permission. en
dc.relation.haspart [Publication 3]: Cássio B. Ribeiro, Esa Ollila, and Visa Koivunen, 2005, Propagation parameter estimation in MIMO systems using mixture of angular distributions model, in Proceedings of the 30th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005), Philadelphia, PA, USA, 18-23 March 2005, volume 4, pages 885-888. © 2005 IEEE. By permission. en
dc.relation.haspart [Publication 4]: Cássio B. Ribeiro, Esa Ollila, and Visa Koivunen, 2007, Stochastic maximum-likelihood method for MIMO propagation parameter estimation, IEEE Transactions on Signal Processing, volume 55, number 1, pages 46-55. © 2007 IEEE. By permission. en
dc.relation.haspart [Publication 5]: Cássio B. Ribeiro, Andreas Richter, and Visa Koivunen, 2005, Stochastic maximum likelihood estimation of angle- and delay-domain propagation parameters, in Proceedings of the 16th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2005), Berlin, Germany, 11-14 September 2005, volume 1, pages 624-628. © 2005 IEEE. By permission. en
dc.relation.haspart [Publication 6]: Cássio B. Ribeiro, Andreas Richter, and Visa Koivunen, 2007, Detecting specular propagation paths in the presence of distributed scattering in angle and delay domains, in Proceedings of the 41st Asilomar Conference on Signals, Systems, and Computers (ACSSC 2007), Pacific Grove, CA, USA, 4-7 November 2007, pages 2259-2263. © 2007 IEEE. By permission. en
dc.relation.haspart [Publication 7]: Cássio B. Ribeiro, Andreas Richter, and Visa Koivunen, 2007, Joint angular- and delay-domain MIMO propagation parameter estimation using approximate ML method, IEEE Transactions on Signal Processing, volume 55, number 10, pages 4775-4790. © 2007 IEEE. By permission. en
dc.subject.other Electrical engineering en
dc.title Propagation parameter estimation in MIMO systems en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.department Signaalinkäsittelyn ja akustiikan laitos fi
dc.subject.keyword multiantenna systems en
dc.subject.keyword parameter estimation en
dc.subject.keyword radio channel modeling en
dc.subject.keyword channel sounding en
dc.identifier.urn URN:ISBN:978-951-22-9303-2
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search archive


Advanced Search

article-iconSubmit a publication

Browse

My Account