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Two-Dimensional Maximum-Likelihood Sequence Detection Is NP Hard

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2 Author(s)
Erik Ordentlich ; Hewlett-Packard Laboratories, Palo Alto, CA, USA ; Ron M. Roth

A 2-D version of the classical maximum-likelihood sequence detection (MLSD) problem is considered for a binary antipodal signal that is corrupted by linear intersymbol interference (ISI) and then passed through a memoryless channel. For 1-D signals and fixed ISI, this detection problem is well-known to be solved using the Viterbi algorithm in time complexity that is linear in the sequence length. It is shown here that, in contrast, the 2-D MLSD problem is NP hard. Specifically, a decision formulation of the problem is shown to be NP complete for a particular 2-D ISI cascaded with either of two memoryless channels: one involving errors and erasures and the other corresponding to additive white Gaussian noise. The proof for the latter case is obtained through a reduction from a still NP complete restricted version of the former. These results are applied to proving the NP completeness of multi user detection under a Toeplitz constraint-a problem known to be equivalent to a variant of 1-D MLSD with growing ISI. This proves a conjecture posed by Verdú in 1989.

Published in:

IEEE Transactions on Information Theory  (Volume:57 ,  Issue: 12 )