Reduced-state sequence estimation of digital sequencesin dispersive channelsusing state partitioning
R.E. Kamel, Y. Bar-Ness
Abstract
R.E. Kamel, Y. Bar-Ness
Abstract
A reduced-state sequence estimator for linear dispersive channels is described. The estimator is based on partitioning the set of all possible channel states in a way that defines a trellis with fewer states, and thus reduces complexity. Such a set partitioning approach provides a good performance/complexity tradeoff. The new technique is a generalisation of that described by Duel-Hallen and Heegard . The Viterbi algorithm (VA) is used to search for the best path through the reduced state trellis.
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A reduced-state sequence estimator for linear dispersive channels is described. The estimator is based on partitioning the set of all possible channel states in a way that defines a trellis with fewer states, and thus reduces complexity. Such a set partitioning approach provides a good performance/complexity tradeoff. The new technique is a generalisation of that described by Duel-Hallen and Heegard . The Viterbi algorithm (VA) is used to search for the best path through the reduced state trellis.
Key concepts: Trellis (graph), Viterbi algorithm, State (computer science), Sequence (biology), Algorithm, Set (abstract data type), Estimator, Channel (broadcasting)