6G networks need LLM-based agents in a layered semantic control plane to achieve autonomous intelligence, with empirical results showing that heterogeneous deployment across device-edge-core is required due to inherent tradeoffs in reasoning, latency, and efficiency.
Implementing neural networks over-the-air via reconfigurable intelligent surfaces,
2 Pith papers cite this work. Polarity classification is still indexing.
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Five heuristic pilot allocation schemes for multi-hop OTA neural inference trade training overhead for classification accuracy under CSI errors, approaching digital performance with sufficient pilots and balanced resources.
citing papers explorer
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6G Needs Agents: Toward Agentic AI-Native Networks for Autonomous Intelligence
6G networks need LLM-based agents in a layered semantic control plane to achieve autonomous intelligence, with empirical results showing that heterogeneous deployment across device-edge-core is required due to inherent tradeoffs in reasoning, latency, and efficiency.
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Pilot Allocation for Multi-Hop Over-the-Air Neural Inference under Imperfect CSI
Five heuristic pilot allocation schemes for multi-hop OTA neural inference trade training overhead for classification accuracy under CSI errors, approaching digital performance with sufficient pilots and balanced resources.