Abstract
A novel method is proposed to resolve collisions in slotted-ALOHA random access schemes that rely on orthogonal modulations at the physical layer, a common choice in wireless sensor networks. The algorithm includes solutions from machine learning, regularized optimization and transportation theory to exploit the symmetry structure that characterizes the signal model at a reasonable computational cost. Simulation results corroborate the effectiveness of the new method as compared to previous solutions.
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