A geometry-aware GPR estimator reconstructs wireless CSI from partial noisy pilots, reducing overhead by up to 75% and training energy by up to 93.75% with competitive error rates.
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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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A Novel Geometry-Aware GPR-Based Energy-Efficient and Low-Overhead Channel Estimation Scheme
A geometry-aware GPR estimator reconstructs wireless CSI from partial noisy pilots, reducing overhead by up to 75% and training energy by up to 93.75% with competitive error rates.
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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.