In many scenarios, side information naturally exists in point-to-point communications. Although side information can be present in the encoder and/or decoder and thus yield several cases, the most important case that worths particular attention is source coding with side information at the decoder (Wyner-Ziv coding) which requires different design strategies compared to the the conventional source coding problem. Due to the difficulty caused by the joint design of random variable and reconstruction function, a common approach to this lossy source coding problem is to apply conventional vector quantization followed by Slepian-Wolf coding. In this thesis, we investigate the best rate-distortion performance achievable asymptotically by practical Wyner-Ziv coding schemes of the above approach from an information theoretic viewpoint and a numerical computation viewpoint respectively.From the information theoretic viewpoint, we establish the corresponding rate-distortion function $\hat{R}_{WZ}(D)$ for any memoryless pair $(X,Y)$ and any distortion measure. Given an arbitrary single letter distortion measure $d$, it is shown that the best rate achievable asymptotically under the constraint that $X$ is recovered with distortion level no greater than $D \geq 0$ is $\hat{R}_{WZ}(D) = \min_{\hat{X}} [I(X; \hat{X}) - I(Y; \hat{X})]$, where the minimum is taken over all auxiliary random variables $\hat{X}$ such that $Ed(X, \hat{X}) \leq D$ and $\hat{X}\to X \to Y$ is a Markov chain.Further, we are interested in designing practical Wyner-Ziv coding. With the characterization at $\hat{R}_{WZ}(D)$, this reduces to investigating $\hat{X}$. Then from the viewpoint of numerical computation, the extended Blahut-Arimoto algorithm is proposed to study the rate-distortion performance, as well as determine the random variable $\hat{X}$ that achieves $\hat{R}_{WZ}(D)$ which provids guidelines for designing practical Wyner-Ziv coding.In most cases, the random variable $\hat{X}$ that achieves $\hat{R}_{WZ}(D)$ is different from the random variable $\hat{X}'$ that achieves the classical rate-distortion $R(D)$ without side information at the decoder. Interestingly, the extended Blahut-Arimoto algorithm allows us to observe an interesting phenomenon, that is, there are indeed cases where $\hat{X} = \hat{X}'$. To gain deep insights of the quantizer's design problem between practical Wyner-Ziv coding and classic rate-distortion coding schemes, we give a mathematic proof to show under what conditions the two random quantizers are equivalent or distinct. We completely settle this problem for the case where ${\cal X}$, ${\cal Y}$, and $\hat{\cal X}$ are all binary with Hamming distortion measure.We also determine sufficient conditions (equivalent condition) for non-binary alphabets with Hamming distortion measure case and Gaussian source with mean-squared error distortion measure case respectively.

In many scenarios, side information naturally exists in point-to-point communications. Although side information can be present in the encoder and/or decoder and thus yield several cases, the most important case that worths particular attention is source coding with side information at the decoder (Wyner-Ziv coding) which requires different design strategies compared to the the conventional source coding problem. Due to the difficulty caused by the joint design of random variable and reconstruction function, a common approach to this lossy source coding problem is to apply conventional vector quantization followed by Slepian-Wolf coding. In this thesis, we investigate the best rate-distortion performance achievable asymptotically by practical Wyner-Ziv coding schemes of the above approach from an information theoretic viewpoint and a numerical computation viewpoint respectively.From the information theoretic viewpoint, we establish the corresponding rate-distortion function $\hat{R}_{WZ}(D)$ for any memoryless pair $(X,Y)$ and any distortion measure. Given an arbitrary single letter distortion measure $d$, it is shown that the best rate achievable asymptotically under the constraint that $X$ is recovered with distortion level no greater than $D \geq 0$ is $\hat{R}_{WZ}(D) = \min_{\hat{X}} [I(X; \hat{X}) - I(Y; \hat{X})]$, where the minimum is taken over all auxiliary random variables $\hat{X}$ such that $Ed(X, \hat{X}) \leq D$ and $\hat{X}\to X \to Y$ is a Markov chain.Further, we are interested in designing practical Wyner-Ziv coding. With the characterization at $\hat{R}_{WZ}(D)$, this reduces to investigating $\hat{X}$. Then from the viewpoint of numerical computation, the extended Blahut-Arimoto algorithm is proposed to study the rate-distortion performance, as well as determine the random variable $\hat{X}$ that achieves $\hat{R}_{WZ}(D)$ which provids guidelines for designing practical Wyner-Ziv coding.In most cases, the random variable $\hat{X}$ that achieves $\hat{R}_{WZ}(D)$ is different from the random variable $\hat{X}'$ that achieves the classical rate-distortion $R(D)$ without side information at the decoder. Interestingly, the extended Blahut-Arimoto algorithm allows us to observe an interesting phenomenon, that is, there are indeed cases where $\hat{X} = \hat{X}'$. To gain deep insights of the quantizer's design problem between practical Wyner-Ziv coding and classic rate-distortion coding schemes, we give a mathematic proof to show under what conditions the two random quantizers are equivalent or distinct. We completely settle this problem for the case where ${\cal X}$, ${\cal Y}$, and $\hat{\cal X}$ are all binary with Hamming distortion measure.We also determine sufficient conditions (equivalent condition) for non-binary alphabets with Hamming distortion measure case and Gaussian source with mean-squared error distortion measure case respectively.