Dipartimento di Ingegneria informatica, automatica e gestionale

The paper studies the max-min fair multicast multigroup beamforming problem in a multi-cell environment, with perfect (instantaneous or statistical) Channel State Information (CSI). We propose a new general distributed algorithmic framework based on INner Convex Approximations (INCA): the nonsmooth NP-hard problem is replaced by a sequence of smooth strongly convex subproblems, which can be solved in a distributed fashion across the cells, with limited communication overhead. Differently from renowned semidefinite-relaxation-based schemes, the INCA algorithm is proved to always converge to a d-stationary solution of the aforementioned class of problems. Numerical results show that it compares favorably with state-of-the-art algorithms.