Estimation of Subspace Occupancy
abstract: The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied...
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ndltd-asu.edu-item-275282018-06-22T03:05:46Z Estimation of Subspace Occupancy abstract: The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied subspace in a multi-user environment from multiple temporal samples of the signal received at a single antenna. These estimators enable identification of resources, such as the orthogonal complement of the occupied subspace, that may be exploitable by an opportunistic user. This concept is supported by simulations showing the estimation of the number of users in a simple CDMA system using a maximum a posteriori (MAP) estimate for the rank. It was found that with suitable parameters, such as high SNR, sufficient number of time epochs and codes of appropriate length, the number of users could be correctly estimated using the MAP estimator even when the noise variance is unknown. Additionally, the process of identifying the maximum likelihood estimate of the orthogonal projector onto the unoccupied subspace is discussed. Dissertation/Thesis Beaudet, Kaitlyn (Author) Cochran, Douglas (Advisor) Turaga, Pavan (Committee member) Berisha, Visar (Committee member) Arizona State University (Publisher) Engineering Cognitive Radio MAP Estimation MIMO Communications Rank Estimation eng 41 pages Masters Thesis Electrical Engineering 2014 Masters Thesis http://hdl.handle.net/2286/R.I.27528 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2014 |
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language |
English |
format |
Dissertation |
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Engineering Cognitive Radio MAP Estimation MIMO Communications Rank Estimation |
spellingShingle |
Engineering Cognitive Radio MAP Estimation MIMO Communications Rank Estimation Estimation of Subspace Occupancy |
description |
abstract: The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied subspace in a multi-user environment from multiple temporal samples of the signal received at a single antenna. These estimators enable identification of resources, such as the orthogonal complement of the occupied subspace, that may be exploitable by an opportunistic user. This concept is supported by simulations showing the estimation of the number of users in a simple CDMA system using a maximum a posteriori (MAP) estimate for the rank. It was found that with suitable parameters, such as high SNR, sufficient number of time epochs and codes of appropriate length, the number of users could be correctly estimated using the MAP estimator even when the noise variance is unknown. Additionally, the process of identifying the maximum likelihood estimate of the orthogonal projector onto the unoccupied subspace is discussed. === Dissertation/Thesis === Masters Thesis Electrical Engineering 2014 |
author2 |
Beaudet, Kaitlyn (Author) |
author_facet |
Beaudet, Kaitlyn (Author) |
title |
Estimation of Subspace Occupancy |
title_short |
Estimation of Subspace Occupancy |
title_full |
Estimation of Subspace Occupancy |
title_fullStr |
Estimation of Subspace Occupancy |
title_full_unstemmed |
Estimation of Subspace Occupancy |
title_sort |
estimation of subspace occupancy |
publishDate |
2014 |
url |
http://hdl.handle.net/2286/R.I.27528 |
_version_ |
1718700638311809024 |