Channel Coding and Source Coding With Increased Partial Side Information

Let (S1,i,S2,i)∼i.i.dp(s1,s2) , i=1,2,⋯ be a memoryless, correlated partial side information sequence. In this work, we study channel coding and source coding problems where the partial side information (S1,S2) is available at the encoder and the decoder, respectively, and, additionally, either the...

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Published in:	Entropy (Basel, Switzerland) Vol. 19; no. 9; p. 467
Main Authors:	Sadeh-Shirazi, Avihay, Basher, Uria, Permuter, Haim
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01-09-2017
Subjects:	Blahut–Arimoto algorithm Channel capacity channel coding Codes Coding Communication channels Computational geometry Convexity Distortion duality Gelfand–Pinsker channel coding Optimization partial side information rate-distortion source coding Wyner-Ziv source coding
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Abstract	Let (S1,i,S2,i)∼i.i.dp(s1,s2) , i=1,2,⋯ be a memoryless, correlated partial side information sequence. In this work, we study channel coding and source coding problems where the partial side information (S1,S2) is available at the encoder and the decoder, respectively, and, additionally, either the encoder’s or the decoder’s side information is increased by a limited-rate description of the other’s partial side information. We derive six special cases of channel coding and source coding problems and we characterize the capacity and the rate-distortion functions for the different cases. We present a duality between the channel capacity and the rate-distortion cases we study. In order to find numerical solutions for our channel capacity and rate-distortion problems, we use the Blahut-Arimoto algorithm and convex optimization tools. Finally, we provide several examples corresponding to the channel capacity and the rate-distortion cases we presented.
AbstractList	Let ( S 1 , i , S 2 , i ) ∼ i . i . d p ( s 1 , s 2 ) , i = 1 , 2 , ⋯ be a memoryless, correlated partial side information sequence. In this work, we study channel coding and source coding problems where the partial side information ( S 1 , S 2 ) is available at the encoder and the decoder, respectively, and, additionally, either the encoder’s or the decoder’s side information is increased by a limited-rate description of the other’s partial side information. We derive six special cases of channel coding and source coding problems and we characterize the capacity and the rate-distortion functions for the different cases. We present a duality between the channel capacity and the rate-distortion cases we study. In order to find numerical solutions for our channel capacity and rate-distortion problems, we use the Blahut-Arimoto algorithm and convex optimization tools. Finally, we provide several examples corresponding to the channel capacity and the rate-distortion cases we presented. Let (S1,i,S2,i)∼i.i.dp(s1,s2) , i=1,2,⋯ be a memoryless, correlated partial side information sequence. In this work, we study channel coding and source coding problems where the partial side information (S1,S2) is available at the encoder and the decoder, respectively, and, additionally, either the encoder’s or the decoder’s side information is increased by a limited-rate description of the other’s partial side information. We derive six special cases of channel coding and source coding problems and we characterize the capacity and the rate-distortion functions for the different cases. We present a duality between the channel capacity and the rate-distortion cases we study. In order to find numerical solutions for our channel capacity and rate-distortion problems, we use the Blahut-Arimoto algorithm and convex optimization tools. Finally, we provide several examples corresponding to the channel capacity and the rate-distortion cases we presented.
Author	Sadeh-Shirazi, Avihay Basher, Uria Permuter, Haim
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Cites_doi	10.1109/TIT.2011.2136910 10.1147/rd.24.0289 10.1109/TIT.2012.2214202 10.1109/TIT.2008.928295 10.1109/TIT.1976.1055508 10.1109/TIT.2006.885500 10.1109/TIT.1985.1057118 10.1109/TIT.2002.1003821 10.1109/TIT.2005.859248 10.1109/TIT.2002.1003843 10.1109/TIT.2005.846422 10.1109/TIT.2016.2533479 10.1109/TIT.1972.1054855 10.1561/0100000025 10.1109/TIT.1972.1054753 10.1109/TIT.2010.2046238 10.1109/TIT.2006.876355 10.1109/TIT.2007.909165 10.1109/TIT.2003.810622 10.1109/TIT.1983.1056723 10.1109/TIT.2005.856978 10.1109/TIT.2013.2266655
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References	ref13 ref12 Csiszar (ref32) 1981 ref15 ref11 ref10 ref1 Shannon (ref14) 1959; 4 ref17 ref16 ref19 ref18 Cover (ref29) 1991 ref23 ref26 ref25 ref20 Gel’fand (ref2) 1980; 9 ref22 ref21 ref28 ref27 ref8 ref7 ref9 ref4 ref3 ref6 ref5 Willems (ref24) 1983 Yeung (ref30) 2008 Berger (ref31) 1978
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Snippet	Let (S1,i,S2,i)∼i.i.dp(s1,s2) , i=1,2,⋯ be a memoryless, correlated partial side information sequence. In this work, we study channel coding and source coding... Let ( S 1 , i , S 2 , i ) ∼ i . i . d p ( s 1 , s 2 ) , i = 1 , 2 , ⋯ be a memoryless, correlated partial side information sequence. In this work, we study...
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SubjectTerms	Blahut–Arimoto algorithm Channel capacity channel coding Codes Coding Communication channels Computational geometry Convexity Distortion duality Gelfand–Pinsker channel coding Optimization partial side information rate-distortion source coding Wyner-Ziv source coding
Title	Channel Coding and Source Coding With Increased Partial Side Information
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