GenSC-6G: A Prototype Testbed for Integrated Generative AI, Quantum, and Semantic Communication
This work provides a scalable resource for developing goal-oriented communication systems in 6G networks, but it is incremental as it focuses on prototyping and dataset creation without major breakthroughs.
The paper tackles the challenge of integrating generative AI, quantum computing, and semantic communication for 6G applications by introducing a prototyping testbed called GenSC-6G, which generates a noise-augmented synthetic dataset to enhance flexibility for tasks like semantic decoding and classification.
We introduce a prototyping testbed, GenSC-6G, developed to generate a comprehensive dataset that supports the integration of generative artificial intelligence (AI), quantum computing, and semantic communication for emerging sixth-generation (6G) applications. The GenSC-6G dataset is designed with noise-augmented synthetic data optimized for semantic decoding, classification, and localization tasks, significantly enhancing flexibility for diverse AI-driven communication applications. This adaptable prototype supports seamless modifications across baseline models, communication modules, and goal-oriented decoders. Case studies demonstrate its application in lightweight classification, semantic upsampling, and edge-based language inference under noise conditions. The GenSC-6G dataset serves as a scalable and robust resource for developing goal-oriented communication systems tailored to the growing demands of 6G networks.