Iterative Waterfilling With User Selection in Gaussian MIMO Broadcast Channels

We consider a sum rate maximization problem with user scheduling in Gaussian MIMO broadcast channels, which is a combinatorial optimization problem. We transform it into a cardinality problem taking into account that selecting inactive users is equivalent to allocating zero power to unselected users. Then, we relax the cardinality constraint by introducing a penalty function to promote sparse power allocation among users. The proposed iterative waterfilling with user selection algorithm is a generalization of the well-known iterative waterfilling that maximizes the sum rate under a sum power constraint in MIMO broadcast channels. Numerical results show that it achieves a very high sum rate with a moderate complexity only proportional to the number of users.