Maximum Likelihood for Colored Noise: Implementing using Viterbi Algorithm

I have a question regarding the ML estimation in presence of colored noise, i.e., Additive Colored Gaussian Noise. I want to implement this using a Viterbi algorithm, since I need to take the 'Correlation Matrix' into account. (Similar to https://dsp.stackexchange.com/a/50777/57695)

$$\mathbf{y} = \mathbf{Hx} + \mathbf{Qn}$$,
where $$\mathbf{H}$$ and $$\mathbf{Q}$$ are the convolutional matrices of the model, $$\mathbf{x}$$ is the transmitted signal, and $$\mathbf{n}$$ is our AWGN. Therefore, $$\mathbf{Qn}$$ is our ACGN.