Convex programming for detection in structured communication problems
The generalized Minimum Mean Squared Error (GMMSE) detector has a bit error rate performance, which is similar to the MMSE detector. The advantage of the GMMSE detector is that it does not require the knowledge of the noise power. However, the computational complexity of the GMMSE detector is signif...
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doaj-e16560763c134942afd59d5826a9407b2020-11-25T00:59:35ZdeuCopernicus PublicationsAdvances in Radio Science 1684-99651684-99732010-12-01830731210.5194/ars-8-307-2010Convex programming for detection in structured communication problemsT. Morsy0J. Götze1H. Nassar2Information Processing Lab., TU Dortmund, 44221 Dortmund, GermanyInformation Processing Lab., TU Dortmund, 44221 Dortmund, GermanyFaculty of Computers and Informatics, Suez Canal University, 41522 Ismailia, EgyptThe generalized Minimum Mean Squared Error (GMMSE) detector has a bit error rate performance, which is similar to the MMSE detector. The advantage of the GMMSE detector is that it does not require the knowledge of the noise power. However, the computational complexity of the GMMSE detector is significantly higher than the computational complexity of the MMSE detector. In this paper, the complexity of the GMMSE detector is reduced by taking into account the structure of the system matrix (Toeplitz). Furthermore, by using circular approximation of the structured system matrix an approximate GMMSE detector is presented, whose computational complexity is only slightly higher than MMSE, i.e.~only an iterative gradient descent algorithm based on the inversion of diagonal matrices is additionally required.http://www.adv-radio-sci.net/8/307/2010/ars-8-307-2010.pdf |
collection |
DOAJ |
language |
deu |
format |
Article |
sources |
DOAJ |
author |
T. Morsy J. Götze H. Nassar |
spellingShingle |
T. Morsy J. Götze H. Nassar Convex programming for detection in structured communication problems Advances in Radio Science |
author_facet |
T. Morsy J. Götze H. Nassar |
author_sort |
T. Morsy |
title |
Convex programming for detection in structured communication problems |
title_short |
Convex programming for detection in structured communication problems |
title_full |
Convex programming for detection in structured communication problems |
title_fullStr |
Convex programming for detection in structured communication problems |
title_full_unstemmed |
Convex programming for detection in structured communication problems |
title_sort |
convex programming for detection in structured communication problems |
publisher |
Copernicus Publications |
series |
Advances in Radio Science |
issn |
1684-9965 1684-9973 |
publishDate |
2010-12-01 |
description |
The generalized Minimum Mean Squared Error (GMMSE) detector has a bit error
rate performance, which is similar to the MMSE detector. The advantage of the
GMMSE detector is that it does not require the knowledge of the noise power.
However, the computational complexity of the GMMSE detector is significantly
higher than the computational complexity of the MMSE detector. In this paper,
the complexity of the GMMSE detector is reduced by taking into account the
structure of the system matrix (Toeplitz). Furthermore, by
using circular approximation of the structured system matrix an approximate
GMMSE detector is presented, whose computational complexity is only slightly
higher than MMSE, i.e.~only an iterative gradient descent algorithm based on
the inversion of diagonal matrices is additionally required. |
url |
http://www.adv-radio-sci.net/8/307/2010/ars-8-307-2010.pdf |
work_keys_str_mv |
AT tmorsy convexprogrammingfordetectioninstructuredcommunicationproblems AT jgotze convexprogrammingfordetectioninstructuredcommunicationproblems AT hnassar convexprogrammingfordetectioninstructuredcommunicationproblems |
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1725217471079645184 |