  In this paper, the sum capacity of the Gaussian Multiple Input Multiple
Output (MIMO) Cognitive Radio Channel (MCC) is expressed as a convex problem
with finite number of linear constraints, allowing for polynomial time interior
point techniques to find the solution. In addition, a specialized class of sum
power iterative waterfilling algorithms is determined that exploits the
inherent structure of the sum capacity problem. These algorithms not only
determine the maximizing sum capacity value, but also the transmit policies
that achieve this optimum. The paper concludes by providing numerical results
which demonstrate that the algorithm takes very few iterations to converge to
the optimum.
