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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/10527

Title: EXIT-constrained BICM-ID Design using Extended Mapping
Authors: Fukawa, Kisho
Ormsub, Soulisak
Tölli, Antti
Anwar, Khoirul
Matsumoto, Tad
Keywords: EXIT Chart
BICM-ID
Mapping
Optimization
Linear Programming
Issue Date: 2012-02-09
Publisher: Springer
Magazine name: EURASIP Journal on Wireless Communications and Networking
Start page: 2012:40
DOI: 10.1186/1687-1499-2012-40
Abstract: This article proposes a novel design framework, EXIT-constrained binary switching algorithm (EBSA), for achieving near Shannon limit performance with single parity check and irregular repetition coded bit interleaved codedmodulation and iterative detection with extended mapping (SI-BICM-ID-EM). EBSA is composed of node degree allocation optimization using linear programming (LP) and labeling optimization based on adaptive binary switching algorithm jointly. This technique achieves exact matching between the Demapper (Dem) and decoder's extrinsic information transfer (EXIT) curves while the convergence tunnel opens until the desired mutual information (MI) point. Moreover, this article proposes a combined use of SI-BICM-ID-EM with Doped-ACCumulator (D-ACC) and modulation doping (MD) to further improve the performance. In fact, the use of D-ACC and SI-BICMID (noted as DSI-BICM-ID-EM) enables the right-most point of the EXIT curve of the combined demapper andD-ACC decoder (Ddacc), denoted as DemDdacc, to reach a point very close to the (1.0, 1.0) MI point. Furthermore,MD provides us with additional degree-of-freedom in “bending” the shape of the demapper EXIT curve bychoosing the mixing ratio of modulation formats, and hence the left most point of the demapper EXIT curve canflexibly be lifted up/pushed down with MD aided DSI-BICM-ID-EM (referred to as MDSI-BICM-ID-EM). Results of the simulations show that near-Shannon limit performance can be achieved with the proposed technique; with aparameter set obtained by EBSA for MDSI-BICM-ID-EM, the threshold signal-to-noise power ratio (SNR) is onlyroughly 0.5 dB away from the Shannon limit, for which the required computational complexity per iteration is atthe same order as a Turbo code with only memory-2 convolutional constituent codes.
Rights: © 2012 Fukawa et al; licensee Springer. Fukawa et al. EURASIP Journal on Wireless Communications and Networking 2012, 2012:40 http://jwcn.eurasipjournals.com/content/2012/1/40 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
URI: http://hdl.handle.net/10119/10527
Material Type: publisher
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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