Sparsifying dictionary analysis for FIR MIMO channel-shortening equalizers
Author | Al-Abbasi, Abubakr O. |
Author | Hamila, Ridha |
Author | Bajwa, Waheed U. |
Author | Al-Dhahir, Naofal |
Available date | 2023-04-04T09:09:06Z |
Publication Date | 2016 |
Publication Name | IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC |
Resource | Scopus |
Abstract | In this paper, we propose a general framework that transforms the problems of designing sparse finite-impulse response channel-shortening equalizers and target impulse response filters for multiple antenna systems into the problems of sparsest-approximation of a vector in different dictionaries. Additionally, we compare several choices of the sparsifying dictionaries in terms of the worst-case coherence metric, which determines their sparsifying effectiveness. Furthermore, a reduced complexity design approach is proposed, which is realized by exploiting the asymptotic equivalence of Toeplitz and circulant matrices. Finally, the significance of our proposed approach is demonstrated through numerical experiments. 2016 IEEE. |
Language | en |
Publisher | IEEE |
Subject | Equalizers Impulse response Wireless telecommunication systems Asymptotic equivalence Circulant matrix Finite impulse response channels Multiple antenna systems Numerical experiments Reduced complexity Target impulse response Worst-case coherences Signal processing |
Type | Conference Paper |
Volume Number | 2016-August |
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Electrical Engineering [2611 items ]