So the future iterations of this algorithm are carried out in exactly the same way. And rather than spending hours and hours and hours going through hundred and hundreds and thousands of those, let's just graph and see what the end result looks like. So this is a computer-generated simulation just showing what we would get if we kept running through those computations over 30 or so iterations. And what you'll see is that, after about somewhere between five and ten, we'll say even ten iterations, that there's no longer any noticeable change in either the power levels, or the SIRs. Because the SIRs are involved in that, which means then the power levels won't change any more, naturally. And so, then we say that we've reached that equilibrium level, and so, it is possible with these SIRs to reach that equilibrium, and we see that after about ten iterations, that is, when we would get there. And so, we can see that overshoot and undershoot pattern in the SIR values for link C, for instance, it starts too low, then it shoots up too high, then it goes down too low, too high, too low, too high, too low, and so on. And then eventually, it hits its matching value to what it needs to be and for link B, the same thing, eventually it hits two, and for link A, it hits it's 1.8 value, which it's trying to get to. And so, you can see how the overshoot and undershoot patterns change from iteration to iteration, and the power levels are doing what they can to compensate for the differences as the SIR stop changing rapidly, the transmit powers also stop changing rapidly. So now, at the end here, we've hit these SIR values 2.2 , 2.0, and 1.8. And so, you can see clearly that the are not anymore changing, the equation that we had, where we had the ratio, times the current power to get the next power. That's not going to change, because now, the ratio for each of these guys is going to approach 1, and once that approaches 1, the next power will be equal to the current power. And is the current, if the current power levels don't change, then the SIRS won't change anymore and that's why we've hit this equilibrium value. So one thing that you notice is that link C has a much higher transmit power than the other two. The other two transmit powers are roughly the same, but link C is much, much higher, it's up here. So why would that be? Let's see if we can intuitively understand why link C would need to transmit much higher. Well, for one thing, we saw that it has the highest noise component, if you looked at it. The noise component is the highest, and that was at 0.3 milliwatts, as opposed to the other ones, so it has the highest noise component, is the first point. The second is that it has the highest interference gains from other links. So the other links had either 0.1 or 0.2, but both of link C's interference gains from A and B were both 0.2, so the interfering gains were the highest. And they were both at 0.2 to be those gains, instead of having 0.1 and 0.2 and so on. And the third point is that it has the highest target SIR value. And that target was 2.2, the other ones were 2.0, and 1.8. So it should make sense that it needs to have the highest transmit power to compensate for these disadvantages in its channel quality.