Sum-Rate Maximization by Iterative User Selection in Cellular Full-Duplex MIMO Systems

The weighted sum-rate problem for full-duplex MIMO networks is an inherently non-convex problem. While state-of-the-art approaches such as successive convex approximation or alternating optimization provide good results, these techniques tend to become slow and computationally expensive as the user number increases. In this contribution, we provide an approach that combines the tasks of user selection and precoder optimization in a single-cell multi-user scenario. Exploiting the bipartite nature of the graph underlying the full-duplex network, we are able to perform a pre-selection of users by efficiently solving an instance of the generalized independent set problem. The final user selection and sum-rate maximization is then achieved by an iterative algorithm based on linear zero-forcing.