Skip to main content
eScholarship
Open Access Publications from the University of California

UC Riverside

UC Riverside Electronic Theses and Dissertations bannerUC Riverside

On Robust and Energy-Limited Joint Source-Channel Coding

Abstract

In this thesis we investigate the lossy transmission of single and bivariate Gaussian sources over bandwidth-mismatched additive Gaussian white noise and broadcast channels. For these scenarios we proposed novel hybrid digital/analog based joint source-channel coding schemes which generalize or outperform existing schemes. In the first scenario we assume that side information is available at the receiver, channel state information of additive interference is available at the transmitter, and power is limited. For this scenario we proposed hybrid digital/analog schemes, for both bandwidth expansion and bandwidth compression cases, which can attain the optimum reconstruction levels. For bandwidth expansion we showed that the scheme can attain optimum distortion levels for a set of receivers with different side information and channel qualities simultaneously with a single set of scheme parameters. In the second scenario, where no side information or interference are present, we consider the robustness of scheme where it must attain the optimal distortion at a target signal-to-noise-ratio and we would like to attain the best distortion pair for two possible receivers one with better and the other with worse channel quality. We extended Tian et al.’s result to a set of non-integer bandwidth expansion ratios. Then we investigate the transmission of bivariate sources over broadcast channels. For this scenario we proposed a scheme which outperforms the known schemes which are either purely digital or hybrid schemes. Finally we analyzed energy-distortion tradeoff for lossy transmission of a Gaussian source over bandwidth-unlimited channel. We performed asymptotical analyses as signal- to-noise-ratio goes to infinity. We also considered zero-delay transmission of the source.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View