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