Group partition for capacity-region-aware device-to-device communications

In this paper, we propose a group partition approach for scalable throughput optimization of capacity-region-aware Device-to-Device communications. Instead of the conventional collision model, we adopt network information theory that allows a receiving device to simultaneously decode multiple packets from multiple transmitting devices, as long as the vector of transmitting rates is inside the capacity region. We propose a novel approach to partition devices into subgroups based on coloring a conflict graph and then solve an optimization problem for each subgroup. In particular, the formation of the conflict graph explicitly takes the capacity region into consideration. Simulation results show that the proposed approach could significantly outperform the greedy algorithm.