A General Framework for the Design and Analysis of Sparse FIR Linear Equalizers
Abstract
Complexity of linear finite-impulse-response (FIR) equalizers is proportional to the square of the number of nonzero taps in the filter. This makes equalization of channels with long impulse responses using either zero-forcing or minimum mean square error (MMSE) filters computationally expensive. Sparse equalization is a widely-used technique to solve this problem. In this paper, a general framework is provided that transforms the problem of sparse linear equalizers (LEs) design into the problem of sparsest-approximation of a vector in different dictionaries. In addition, some possible choices of sparsifying dictionaries in this framework are discussed. Furthermore, the worst-case coherence of some of these dictionaries, which determines their sparsifying strength, are analytically and/or numerically evaluated. Finally, the usefulness of the proposed framework for the design of sparse FIR LEs is validated through numerical experiments.
Keywords
Cite
@article{arxiv.1511.06971,
title = {A General Framework for the Design and Analysis of Sparse FIR Linear Equalizers},
author = {Abubakr O. Al-Abbasi and Ridha Hamila and Waheed U. Bajwa and Naofal Al-Dhahir},
journal= {arXiv preprint arXiv:1511.06971},
year = {2018}
}
Comments
7 pages, 4 figures, IEEE GlobalSIP'15 Conference