A Rate-Splitting Strategy for Max-Min Fair Multigroup Multicasting

We consider the problem of transmit beamforming to multiple cochannel multicast groups. The conventional approach is to beamform a designated data stream to each group, while treating potential inter-group interference as noise at the receivers. In overloaded systems where the number of transmit antennas is insufficient to perform interference nulling, we show that inter-group interference dominates at high SNRs, leading to a saturating max-min fair performance. We propose a rather unconventional approach to cope with this issue based on the concept of Rate-Splitting (RS). In particular, part of the interference is broadcasted to all groups such that it is decoded and canceled before the designated beams are decoded. We show that the RS strategy achieves significant performance gains over the conventional multigroup multicast beamforming strategy.Comment: accepted to the 17th IEEE International workshop on Signal Processing advances in Wireless Communications (SPAWC 2016

Interference Alignment-Aided Base Station Clustering using Coalition Formation

Base station clustering is necessary in large interference networks, where the channel state information (CSI) acquisition overhead otherwise would be overwhelming. In this paper, we propose a novel long-term throughput model for the clustered users which addresses the balance between interference mitigation capability and CSI acquisition overhead. The model only depends on statistical CSI, thus enabling long-term clustering. Based on notions from coalitional game theory, we propose a low-complexity distributed clustering method. The algorithm converges in a couple of iterations, and only requires limited communication between base stations. Numerical simulations show the viability of the proposed approach.Comment: 2nd Prize, Student Paper Contest. Copyright 2015 SS&C. Published in the Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, Nov 8-11, 2015, Pacific Grove, CA, US