Sequence detection for binary ISI channels using signal-space partitioning

Abstract

Binary symbol detection based on a sequence of finite observation signals is formulated in the multidimensional signal space. A systematic space partitioning method is proposed to divide the entire space into two decision regions using a set of hyperplanes, The resulting detector structure consists of K parallel linear classifiers followed by a K-to-1 Boolean mapper, and is well suited to high-speed implementation. Compared to direct implementation of the fixed-delay tree search (FDTS) detection rule, the proposed signal-space formulation results in a considerable saving in digital hardware. Examples taken from binary-input intersymbol interference (ISI) channels are used to demonstrate the proposed technique. Block processing strategies suitable for high-speed applications are also discussed.