A little more detail about the experimental design would help. But my guess is that since each subject completes both trials, then each subject probably has a time=1 value for trial 1 as well as a time=1 value for trial 2. If that is correct, then you have two time=1 values (as well as two time=2 values and two time=0 or two time=3 values) for each subject. This will produce the infinite likelihood error.
In order to produce the 6x6 unstructured covariance structure in which the first three rows of the covariance matrix represent the residual variance structure for trial 1 at the three time points and the last three rows of the covariance matrix represent the residual variance structure for trial 2 over the three time points, you can change your REPEATED statement to:
repeated trial*time / subject=subject type=un r rcorr;
But maybe you are thinking of an R matrix which assumes that the residuals for trials 1 and 2 are independent of one another, and that the covariance over time within each of the two trials is the same. In order to fit that model, you would specify:
repeated time / subject=subject*trial type=un r rcorr;
With each subject producing a response for each of the two trials, you should have employed a cross-over design for your experiment. I don't see anything in your model which accounts for period effects that would indicate whether trial 1 was administered first or trial 2 was administered first. So, either your experimental design has a severe shortcoming, or your model of the fixed effects is not appropriately specified.
HTH