A Centralized Repetition Selection Scheme for Dense In-X Subnetworks

Packet repetitions combined with frequency channel hopping is a promising solution for improving reliability in dense in-X subnetwork deployments. In this paper, we propose a centralized repetition selection (C-Rep) scheme where a controller selects the number of packet repetitions to be used by each subnetwork based on the interference coupling. We first derive the optimal and near optimal average failure probability of the presented scheme, and propose a low complexity empirical cost function to be minimized via a genetic algorithm. Simulation results highlight the capability of C-Rep of reducing the failure probability in the subnetwork deployment by a factor of ∼ ×10 and above with respect to benchmark methods with optimized fixed number of packet repetitions. The empirically defined cost function leads to similar performance as when the near-optimal failure probability is used as a cost function, while reducing the number of calculations by a factor of above ∼ ×40. Robustness of the proposed scheme to different radio propagation conditions has also been verified.