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Lossy Coding of Correlated Sources Over a Multiple Access Channel: Necessary Conditions and Separation Results
- Source :
- IEEE Transactions on Information Theory
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- Lossy coding of correlated sources over a multiple access channel (MAC) is studied. First, a joint source-channel coding scheme is presented when the decoder has correlated side information. Next, the optimality of separate source and channel coding, that emerges from the availability of a common observation at the encoders, or side information at the encoders and the decoder, is investigated. It is shown that separation is optimal when the encoders have access to a common observation whose lossless recovery is required at the decoder, and the two sources are independent conditioned on this common observation. Optimality of separation is also proved when the encoder and the decoder have access to shared side information conditioned on which the two sources are independent. These separation results obtained in the presence of side information are then utilized to provide a set of necessary conditions for the transmission of correlated sources over a MAC without side information. Finally, by specializing the obtained necessary conditions to the transmission of binary and Gaussian sources over a MAC, it is shown that they can potentially be tighter than the existing results in the literature, providing a novel converse for this fundamental problem.<br />Comment: Accepted to appear in IEEE Transactions on Information Theory on May 19, 2018
- Subjects :
- FOS: Computer and information sciences
Technology
conditional independence
Computer science
Computer Science - Information Theory
RATE-DISTORTION FUNCTION
Gaussian
SIDE INFORMATION
multiple access channel
COMMUNICATION
Data_CODINGANDINFORMATIONTHEORY
02 engineering and technology
Library and Information Sciences
separation theorem
symbols.namesake
Engineering
joint source and channel coding
Distortion
0801 Artificial Intelligence and Image Processing
1005 Communications Technologies
0202 electrical engineering, electronic engineering, information engineering
hybrid coding
Computer Science::Information Theory
Lossy coding
Lossless compression
rate-distortion theory
Channel code
Science & Technology
Computer Science, Information Systems
Common information
Information Theory (cs.IT)
Engineering, Electrical & Electronic
020206 networking & telecommunications
Computer Science Applications
0906 Electrical and Electronic Engineering
Computer Science
DECODER
symbols
Networking & Telecommunications
Encoder
Algorithm
Decoding methods
Information Systems
Communication channel
Subjects
Details
- ISSN :
- 15579654 and 00189448
- Volume :
- 64
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Information Theory
- Accession number :
- edsair.doi.dedup.....57913674c51dfad085456226ad9d401a
- Full Text :
- https://doi.org/10.1109/tit.2018.2844833