  The last couple of years have seen an ever-increasing interest in using
different Ising solvers, like Quantum annealers, Coherent Ising machines, and
Oscillator-based Ising machines, for solving tough computational problems in
various domains. Although the simulations predict massive performance
improvements for several tough computational problems, the real implementations
of the Ising solvers tend to have limited precision, which can cause
significant performance deterioration. This paper presents a novel methodology
for mapping the problem on the Ising solvers to artificially increase the
effective precision. We further evaluate our method for the
Multiple-Input-Multiple-Output signal detection problem.
