Trellis-based equalization for sparse ISI channels revisited

• Main Authors: Mietzner, J., Badri-Hoeher, S., Land, I., Hoeher, P.A.
• Format: Conference Proceeding
• Language: English
• Subjects: Codes; Computational complexity; Decision feedback equalizers; Finite impulse response filter; Intersymbol interference; Land mobile radio; Maximum likelihood estimation; Nonlinear filters; Viterbi algorithm; World Wide Web
• ISSN: 2157-8095; 2157-8117
• DOI: 10.1109/ISIT.2005.1523328

Sparse intersymbol-interference (ISI) channels are encountered in a variety of high-data-rate communication systems. Such channels have a large channel memory length, but only a small number of significant channel coefficients. In this paper, trellis-based equalization of sparse ISI channels is revisited. Due to the large channel memory length, the complexity of maximum-likelihood detection, e.g., by means of the Viterbi algorithm (VA), is normally prohibitive. In the first part of the paper, a unified framework based on factor graphs is presented for complexity reduction without loss of optimality. In this new context, two known reduced-complexity algorithms for sparse ISI channels are recapitulated: The multi-trellis VA (M-VA) and the parallel-trellis VA (P-VA). It is shown that the M-VA, although claimed, does not lead to a reduced computational complexity. The P-VA, on the other hand, leads to a significant complexity reduction, but can only be applied for a certain class of sparse channels. In the second part of the paper, a unified approach is investigated to tackle general sparse channels: it is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalizer algorithms feasible, without significant loss of optimality. Numerical results verify the efficiency of the proposed receiver structure