Hamming distance preserving mappings and trellis codes with constrained binary symbols

The transformation of a linear convolutional code into a run-length-constrained or balanced trellis code with the same or larger free distance is investigated. The transformation involves a Hamming-distance-preserving mapping of the set of unconstrained binary symbols of the convolutional code onto a set of suitably constrained symbols. Simple tests to determine if these mappings can exist and a tree search algorithm for finding such mappings are presented.<
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