Ant Colony Optimization for resource sharing among D2D communications

Device-to-Device (D2D) communication has been recently devised as a new paradigm that boosts spectrum reuse inside a cell, leading to enhanced quality of service and user experience. The design of proper D2D resource allocation schemes, which constitute the enablers towards this direction, is an open challenge. In this paper, we propose a D2D resource allocator based on the Ant Colony Optimization (ACO) theory. ACO is exploited towards identifying interference isolated D2D links that can safely share the same resources, consulting a graph representation of the network. Simulation studies demonstrate the self-learning nature of this method, which results to a comparable performance to that of an optimal resource allocator of significantly higher computational complexity.