The Parametrized Complexity of Some Fundamental Problems in Coding Theory

The parametrized complexity of a number of fundamental problems in the theory of linear codes and integer lattices is explored. Concerning codes, the main results are that MAXIMUM-LIKELIHOOD DECODING and WEIGHT DISTRUBUTION are hard for the parametrized complexity class W[1]. The NP-completeness of these two problems was established by Berlekamp, McEliece, and van Tilborg in 1978 using by means of a reduction from THREE-DIMENSIONAL MATCHING. On the other hand, our proof of hardness for W[1] is based on a parametric polynomial-time transformation from PERFECT CODE in graphs. An immediate consequence of our results is that bounded-distance decoding is likely to be hard for binary linear codes. Concerning lattices, we address the THETA SERIES problem of determining for an integer lattice $\L$ %given by a set of generators, and a positive integer k whether there is a vector $x \in \L$ of Euclidean norm k. We prove here for the first time that THETA SERIES is NP-complete and show that it is also hard for W[1]. Furthermore, we prove that the NEAREST VECTOR problem for integer lattices is hard for W[1]. These problems are the counterparts of WEIGHT DISTRUBUTION and MAXIMUM-LIKELIHOOD DECODING for lattices. Relations between all these problems and combinatorial problems in graphs are discussed.