Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Matthew C. Valenti.


Channel capacity is an important aspect of every digital communication system. Capacity can be defined as the highest rate of information that can be transmitted over the channel with low error probability. The purpose of this research is to study the effect of the input symbol distribution on the information rate when the signal is transmitted over an Additive White Gaussian Noise (AWGN) channel with a quantized output. The channel was analyzed by transforming it into a Discrete Memoryless Channel (DMC), which is a discrete-input and discrete-output channel. Given the quantizer resolution and Signal-to-Noise Ratio (SNR), this thesis proposes a strategy for achieving the capacity of a certain shaping technique previously proposed by Le Goff, et al. Under the constraints of the modulation, the shaping technique, and the quantizer resolution, the capacity is found by jointly optimizing the input distribution and quantizer spacing. The optimization is implemented by exhaustively searching over all feasible input distributions and a finely-spaced set of candidate quantizer spacings. The constrained capacity for 16-QAM modulation is found using the proposed technique.