Reproduce “The Role of Generative Artificial Intelligence in Testing and Automation of Open RAN Systems: GNG-OTA Framework” on OpenResearch
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About this paper
Aly Sabri Abdalla, Vuk Marojevic
GNG-OTA proposes a workflow for O-RAN interoperability and performance testing. It uses natural-language processing (NLP) to turn requirements into test steps, a generative adversarial network (GAN) to generate synthetic traffic, and a graph neural network (GNN) to compare test interactions with historical graphs. The paper reports no implementation or measured improvement, so benefits remain intended rather than demonstrated.
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