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.
Song, P., Scutari, G., Facchinei, F., Lampariello, L. (2016). D3M: Distributed multi-cell multigroup multicasting. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp.3741-3745). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICASSP.2016.7472376].
D3M: Distributed multi-cell multigroup multicasting
LAMPARIELLO, LORENZO
2016-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
