The work establishes two proxies linking AirComp distortion to inference quality and derives threshold-based and dual-decomposition power allocations for TDM and FDM modes in an integrated sensing and edge AI system.
Optimized power control for over-the-air computation in fading channels,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.SP 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
A Bayesian distributed ISEA system uses a Gaussian-mixture prior for an RWB estimator at sensing and derives threshold-based optimal power allocation at communication to gain inference performance.
A structured survey of edge perception that integrates sensing modalities, edge AI, task-driven designs, and open challenges for 6G networks.
citing papers explorer
-
Optimized Power Control for Multi-User Integrated Sensing and Edge AI
The work establishes two proxies linking AirComp distortion to inference quality and derives threshold-based and dual-decomposition power allocations for TDM and FDM modes in an integrated sensing and edge AI system.
-
Distributed Integrated Sensing and Edge AI Exploiting Prior Information
A Bayesian distributed ISEA system uses a Gaussian-mixture prior for an RWB estimator at sensing and derives threshold-based optimal power allocation at communication to gain inference performance.
-
Sense Smarter, Think Better: Edge Perception for Next-Generation Networks
A structured survey of edge perception that integrates sensing modalities, edge AI, task-driven designs, and open challenges for 6G networks.