# Distributed Integrated Sensing and Edge AI Exploiting Prior Information

arXiv: https://arxiv.org/abs/2512.00309 · HTML: https://mlsanity.com/paper/2512.00309/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Nov 2025.

## Built on by (most cited first, 1 of 1)

- [From Digital Twins to World Models:Opportunities, Challenges, and Applications for Mobile Edge General Intelligence](https://mlsanity.com/paper/2603.17420/) (2026)

## Abstract (arXiv)

This paper investigates a distributed ISEA system under a Bayesian framework, focusing on incorporating task-relevant priors to maximize inference performance. At the sensing level, an RWB estimator with a GM prior is designed. By weighting class-conditional posterior means with responsibilities, RWB effectively denoises features and outperforms ML at low SNR. At the communication level, two theoretical proxies are introduced: the computation-optimal and decision-optimal proxies. Optimal transceiver designs in terms of closed-form power allocation are derived for both TDM and FDM settings, revealing threshold-based and dual-decomposition structures. Results show that the discriminant-aware allocation yields additional inference gains.