The Worst-Case DFT Filter Bank Design with Sub-channel Variations

In this paper, we consider an optimal design of a DFT filter bank subject to subchannel variation constraints. The design problem is formulated as a minimax optimization problem. By exploiting the properties of this minimax optimization problem, we show that it is equivalent to a semi-infinite optim...

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Main Authors: Jiang, L., Wu, Changzhi, Wang, Xiangyu, Teo, Kok Lay
Other Authors: Honglei Xu
Format: Book Chapter
Published: Springer 2015
Online Access:http://link.springer.com/chapter/10.1007/978-3-662-47044-2_10#page-1
http://hdl.handle.net/20.500.11937/36573
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author Jiang, L.
Wu, Changzhi
Wang, Xiangyu
Teo, Kok Lay
author2 Honglei Xu
author_facet Honglei Xu
Jiang, L.
Wu, Changzhi
Wang, Xiangyu
Teo, Kok Lay
author_sort Jiang, L.
building Curtin Institutional Repository
collection Online Access
description In this paper, we consider an optimal design of a DFT filter bank subject to subchannel variation constraints. The design problem is formulated as a minimax optimization problem. By exploiting the properties of this minimax optimization problem, we show that it is equivalent to a semi-infinite optimization problem in which the continuous inequality constraints are only with respect to frequency. Then, a computational scheme is developed to solve such a semi-infinite optimization problem. Simulation results show that, for a fixed distortion level, the aliasing level between different subbands is significantly reduced, in some cases up to 28 dB, when compared with that obtained by the bi-iterative optimization method without consideration of the subchannel variations.
first_indexed 2025-11-14T08:46:17Z
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institution Curtin University Malaysia
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last_indexed 2025-11-14T08:46:17Z
publishDate 2015
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spelling curtin-20.500.11937-365732023-02-27T07:34:28Z The Worst-Case DFT Filter Bank Design with Sub-channel Variations Jiang, L. Wu, Changzhi Wang, Xiangyu Teo, Kok Lay Honglei Xu Song Wang Soon-Yi Wu In this paper, we consider an optimal design of a DFT filter bank subject to subchannel variation constraints. The design problem is formulated as a minimax optimization problem. By exploiting the properties of this minimax optimization problem, we show that it is equivalent to a semi-infinite optimization problem in which the continuous inequality constraints are only with respect to frequency. Then, a computational scheme is developed to solve such a semi-infinite optimization problem. Simulation results show that, for a fixed distortion level, the aliasing level between different subbands is significantly reduced, in some cases up to 28 dB, when compared with that obtained by the bi-iterative optimization method without consideration of the subchannel variations. 2015 Book Chapter http://hdl.handle.net/20.500.11937/36573 http://link.springer.com/chapter/10.1007/978-3-662-47044-2_10#page-1 Springer restricted
spellingShingle Jiang, L.
Wu, Changzhi
Wang, Xiangyu
Teo, Kok Lay
The Worst-Case DFT Filter Bank Design with Sub-channel Variations
title The Worst-Case DFT Filter Bank Design with Sub-channel Variations
title_full The Worst-Case DFT Filter Bank Design with Sub-channel Variations
title_fullStr The Worst-Case DFT Filter Bank Design with Sub-channel Variations
title_full_unstemmed The Worst-Case DFT Filter Bank Design with Sub-channel Variations
title_short The Worst-Case DFT Filter Bank Design with Sub-channel Variations
title_sort worst-case dft filter bank design with sub-channel variations
url http://link.springer.com/chapter/10.1007/978-3-662-47044-2_10#page-1
http://hdl.handle.net/20.500.11937/36573