Distributed Quantizer Linear Coding (DQLC) is a joint source-channel coding scheme that encodes and transmits distributed Gaussian sources over a MAC under severe delay constraints, providing significant gains when compared to uncoded transmissions. DQLC, however, relies on the appropriate optimization of its parameters depending on source correlation, channel state and noise variance. In this work, we propose a parameter optimization strategy that relies on the lattice structure of the mapping, reduces the number of parameters to estimate, and exhibits lower computational complexity.