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Please use this identifier to cite or link to this item: http://hdl.handle.net/1974/1207

Title: Joint Source-Channel Coding Reliability Function for Single and Multi-Terminal Communication Systems
Authors: Zhong, Yangfan

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Keywords: Asymmetric 2-user source-channel system, common and private message, common randomization, continuous memoryless sources and channels, correlated sources, discrete memoryless sources and channels, error exponent, excess distortion exponent, feedback, Fenchel transform, probability of error, probability of excess distortion, Fenchel duality theorem, Hamming distortion measure, joint source-channel coding, Markov types, memoryless Gaussian and Laplacian sources, multiple-access channel, reliability function, separation principle, source side information, squared/magnitude-error distortion, stationary ergodic Markov source/channel, tandem coding, type packing lemma.
Common and private message
Common randomization
Continuous memoryless sources and channels
Correlated sources
Discrete memoryless sources and channels
Error exponent
Excess distortion exponent
Feedback
Fenchel transform
Probability of error
Probability of excess distortion
Fenchel duality theorem
Hamming distortion measure
Joint source-channel coding
Markov types
Memoryless Gaussian and Laplacian sources
Multiple-access channel
Reliability function
Separation principle
Source side information/squared/magnitude-error distortion
Stationary ergodic Mrkov source/channel
Tandem coding
Type packing lemma
Broadcast channel
Issue Date: 2008
Series/Report no.: Canadian theses
Abstract: Traditionally, source coding (data compression) and channel coding (error protection) are performed separately and sequentially, resulting in what we call a tandem (separate) coding system. In practical implementations, however, tandem coding might involve a large delay and a high coding/decoding complexity, since one needs to remove the redundancy in the source coding part and then insert certain redundancy in the channel coding part. On the other hand, joint source-channel coding (JSCC), which coordinates source and channel coding or combines them into a single step, may offer substantial improvements over the tandem coding approach. This thesis deals with the fundamental Shannon-theoretic limits for a variety of communication systems via JSCC. More specifically, we investigate the reliability function (which is the largest rate at which the coding probability of error vanishes exponentially with increasing blocklength) for JSCC for the following discrete-time communication systems: (i) discrete memoryless systems; (ii) discrete memoryless systems with perfect channel feedback; (iii) discrete memoryless systems with source side information; (iv) discrete systems with Markovian memory; (v) continuous-valued (particularly Gaussian) memoryless systems; (vi) discrete asymmetric 2-user source-channel systems. For the above systems, we establish upper and lower bounds for the JSCC reliability function and we analytically compute these bounds. The conditions for which the upper and lower bounds coincide are also provided. We show that the conditions are satisfied for a large class of source-channel systems, and hence exactly determine the reliability function. We next provide a systematic comparison between the JSCC reliability function and the tandem coding reliability function (the reliability function resulting from separate source and channel coding). We show that the JSCC reliability function is substantially larger than the tandem coding reliability function for most cases. In particular, the JSCC reliability function is close to twice as large as the tandem coding reliability function for many source-channel pairs. This exponent gain provides a theoretical underpinning and justification for JSCC design as opposed to the widely used tandem coding method, since JSCC will yield a faster exponential rate of decay for the system error probability and thus provides substantial reductions in complexity and coding/decoding delay for real-world communication systems.
Description: Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2008-05-13 22:31:56.425
URI: http://hdl.handle.net/1974/1207
Appears in Collections:Queen's Theses & Dissertations
Mathematics & Statistics Graduate Theses

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