Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Equalization of Sparse Intersymbol-Interference Channels Revisited | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2006 Article ID 29075 Pages 1-13 DOI WCN 2006 29075 Equalization of Sparse Intersymbol-Interference Channels Revisited Jan Mietzner 1 Sabah Badri-Hoeher 1 Ingmar Land 2 and Peter A. Hoeher1 1 Information and Coding Theory Lab ICT Faculty of Engineering University of Kiel Kaiserstrasse 2 24143 Kiel Germany 2 Department of Communication Technology Digital Communications Division Aalborg University Frederik Bajers Vej 7 A3 Aalborg East 9220 Denmark Received 18 April 2005 Revised 12 January 2006 Accepted 28 February 2006 Recommended for Publication by Brian Sadler Sparse intersymbol-interference ISI channels are encountered in a variety of communication systems especially in high-data-rate systems. These channels have a large memory length but only a small number of significant channel coefficients. In this paper equalization of sparse ISI channels is revisited with focus on trellis-based techniques. Due to the large channel memory length the complexity of maximum-likelihood sequence estimation by means of the Viterbi algorithm 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 trellis-based techniques are recapitulated. In the second part of the paper a simple alternative approach is investigated to tackle general sparse ISI channels. It is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalization techniques feasible without significant loss of optimality. Copyright 2006 Jan Mietzner et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Sparse .
