We consider the problem of finding the least-squares solution to a system of linear equations where the unknown vector has integer entries (or, more precisely, has entries belonging to a subset of the integers), yet where the coefficient matrix and given vector are comprised of real numbers. Geometrically, this problem is equivalent to finding the closest lattice point to a given point and is known to be NP hard. In communication applications, however, the given vector is not arbitrary, but is a lattice point perturbed by some noise vector. Therefore it is of interest to study the computational complexity of various algorithms as a function of the noise variance or, often more appropriately, the SNR.