Multidimensional signal space partitioning using a minimal set of hyperplanes for detecting ISI-corrupted symbols. - Younggyun Kim
A signal space partitioning technique is presented for detecting symbols transmitted through intersymbol interference channels. The decision boundary is piecewise linear and is made up of several hyperplanes. The goal here is to minimize the number of hyperplanes for a given performance measure, namely, the minimum distance between any signal and the decision boundary, Unlike in Voronoi partitioning, individual hyperplanes are chosen to separate signal clusters rather than signal pairs. The convex regions associated with individual signals, which together form the overall decision region, generally overlap or coincide among in-class signals. The technique leads to an asymptotically optimum detector when the target distance is set at half the minimum distance associated with the maximum-likelihood sequence detector. Complexity and performance can be easily traded as the target distance is a flexible design parameter
Keywords: ISI; ISI-corrupted symbols detection; Voronoi partitioning; Asymptotically optimum detector; Complexity; Convex regions; Decision region; Design parameter; Finite impulse response; Hyperplanes; In-class signals; Intersymbol interference channels; Maximum-likelihood sequence detector; Minimal set; Minimum distance; Multidimensional signal space partitioning; Performance; Performance measure; Piecewise linear decision boundary; Signal clusters separation; Signal space detector; Signal space partitioning; Symbol-error probability; Target distance