Title:
Hyper-wideband OFDM system

dc.contributor.advisor Ralph, Stephen E.
dc.contributor.advisor Barry, John R.
dc.contributor.advisor Romberg, Justin
dc.contributor.author Tan, Edward S.
dc.contributor.department Electrical and Computer Engineering
dc.date.accessioned 2016-05-27T13:25:05Z
dc.date.available 2016-05-27T13:25:05Z
dc.date.created 2016-05
dc.date.issued 2016-05-02
dc.date.submitted May 2016
dc.date.updated 2016-05-27T13:25:05Z
dc.description.abstract Hyper-wideband communications represent the next frontier in spread spectrum RF systems with an excess of 10 GHz instantaneous bandwidth. In this thesis, an end-to-end physical layer link is implemented featuring 16k-OFDM with a 4 GHz-wide channel centered at 9 GHz. No a priori channel state information is assumed; channel information is derived from the preamble and comb pilot structure. Due to the unique expansive spectral properties, the channel estimator is primarily composed of least squares channel estimates combined with a robust support vector statistical learning approach using autonomously selected parameters. The system’s performance is demonstrated through indoor wireless experiments, including line-of-sight and near-line-of-sight links. Moreover, it is shown that the support vector approach performs superior to linear and cubic spline inter/extrapolation of the least squares channel estimates.
dc.description.degree M.S.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/55056
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject OFDM
dc.subject Support vector regression
dc.subject Hyper-wideband
dc.title Hyper-wideband OFDM system
dc.type Text
dc.type.genre Thesis
dspace.entity.type Publication
local.contributor.advisor Romberg, Justin
local.contributor.advisor Barry, John R.
local.contributor.advisor Ralph, Stephen E.
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
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relation.isAdvisorOfPublication 85c8609c-9493-4eb5-9b86-d5ebdc5747bb
relation.isAdvisorOfPublication af493194-eca1-4e90-a38f-3433f593f11b
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relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Masters
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