ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms. (arXiv:2112.09559v2 [cs.NI] UPDATED)

In spite of the new opportunities brought about by the Open RAN, advances in
ML-based network automation have been slow, mainly because of the
unavailability of large-scale datasets and experimental testing infrastructure.
This slows down the development and widespread adoption of Deep Reinforcement
Learning (DRL) agents on real networks, delaying progress in intelligent and
autonomous RAN control. In this paper, we address these challenges by proposing
practical solutions and software pipelines for the design, training, testing,
and experimental evaluation of …

arxiv experimental learning machine machine learning platforms