UC Riverside

This thesis focuses on the communication of a low bandwidth Gaussian source with specific energy restrictions through an AWGN channel. Since the source has low bandwidth, it is assumed that the transmitter is capable of delivering many dimensions per symbol without any loss of information. The offered schemes use high resolution quantization which requires an optimization of the MSE distortion to reach optimality. Several practical schemes with ML estimator and orthogonal modulation are used with different types of (high resolution) quantizers so that the distortion expression can be derived analytically. Due to the cumbersome in analytically expressing the distortion for MMSE estimation, MMSE estimator is offered under suboptimal conditions. To increase the performance of the MMSE estimator, an iterative design algorithm that transitions between receiver and transmitter is introduced. The algorithm assumes that the decoder is applying ML rule and it optimizes the quantizer's point density function accordingly. Then it fixes the transmitter side and runs Monte Carlo Simulations using MMSE estimator in a bounded set of points in the variables' space in search of the minimum distortion.