DocumentCode :
3303060
Title :
Improved decoding of Shannon-Kotel´nikov mappings
Author :
Rüngeler, Matthias ; Schotsch, Birgit ; Vary, Peter
Author_Institution :
Inst. of Commun. Syst. & Data Process. (iNd), RWTH Aachen Univ., Aachen, Germany
fYear :
2010
fDate :
17-20 Oct. 2010
Firstpage :
633
Lastpage :
638
Abstract :
In some applications the transmission of discrete-time but continuous-amplitude (or multilevel) source symbols is required which might be more bandwidth efficient than conventional digital transmission. An appropriate method is to apply a source channel mapping (SCM) of M source symbols to N channel symbols. A geometrical approach for SCM has been introduced by Shannon and Kotel´nikov (Shannon-Kotel´nikov mappings). These systems are used to map M continuous-amplitude and discrete-time source symbols to N continuous-amplitude and discrete-time channel symbols without the intermediate step of a binary representation. These schemes are usually decoded using a maximum likelihood (ML) decoder which leads to optimum results in the mean square error sense for very good channels, but is suboptimal for noisy channels. In this paper the performance of an improved decoder, the minimum mean square error (MMSE) decoder is assessed. As a special case of a 1:2 expansion case (rate 1/2) Shannon-Kotel´nikov mapping, the Archimedes spiral is considered. The properties of the ML and MMSE decoder are examined and a graphical interpretation of the superior performance of the MMSE decoder is given. Furthermore, the robustness of the MMSE decoder w.r.t. an inaccurate estimation of the channel quality is determined. The concepts of the MMSE decoder which lead to a superior performance to the ML decoder can be generalized and applied to all Shannon-Kotel´nikov mappings.
Keywords :
combined source-channel coding; least mean squares methods; maximum likelihood decoding; M continuous-amplitude; M source symbols; ML decoder; MMSE decoder; N channel symbols; N continuous-amplitude; Shannon-Kotel´nikov mappings; binary representation; channel quality; continuous-amplitude source symbols; digital transmission; discrete-time channel source symbols; discrete-time transmission; geometrical approach; maximum likelihood decoder; minimum mean square error decoder; source channel mapping; AWGN channels; Approximation methods; Decoding; Maximum likelihood estimation; Noise; Spirals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory and its Applications (ISITA), 2010 International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-6016-8
Electronic_ISBN :
978-1-4244-6017-5
Type :
conf
DOI :
10.1109/ISITA.2010.5649697
Filename :
5649697
Link To Document :
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