Finite-Length Signal Quantization using Discrete Optimization

This paper introduces a novel, discrete optimization based method for the computation of coarsely quantized, oversampled finite-length digital signals. The method, while only suitable for offline computation, is more general than the established sigma-delta encoding technique, due to its capacity to take into account complex specifications and design trade-offs. Signal generation is formulated as a linearly constrained, convex, integer quadratic programming problem which is solved through an application specific branch-and-bound algorithm. The optimization method is illustrated with a fractional-N frequency synthesizer based modulator design example.